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Integrating Teams of Mobile Robots in Wireless Ad-Hoc Networks
Proceedings of the 2009 IFAC Workshop on Networked Robotics Golden, CO, USA, October 6-8, 2009
Integrating Teams of Mobile Robots in Wireless Ad-Hoc Networks Florian Zeiger ∗ Markus Sauer ∗ Lothar Stolz ∗ Klaus Schilling ∗∗ Center for Telematics, W¨ urzburg , Germany (e-mail: {florian.zeiger,markus.sauer,lothar.stolz}@telematik-zentrum.de). ∗∗ Department of Computer Science - Robotics and Telematics, University of W¨ urzburg, W¨ urzburg , Germany (e-mail: {schi}@informatik.uni-wuerzburg.de). ∗
Abstract: Modern applications of mobile robot teams or robot teleoperation often demand wireless any-to-any communication in combination with highly dynamical network topologies to accomplish more and more complex tasks. These communication systems should also not rely on any pre-existing infrastructure, have low costs, and should allow for a seamless integration into existing communication networks. The well tested technology IEEE 802.11 wireless LAN offers all these possibilities. Especially the capability of realizing ad-hoc networks offers a high potential for WLAN to be used in the area of networked robots. Mesh networks and mobile ad-hoc networks are able to provide mechanisms for realizing stable communication links for networked robots. This work gives a brief overview on mesh networks and ad-hoc networks and further shows the behavior of different ad-hoc routing protocols (AODV, OLSR, DSR, BATMAN) in typical scenarios for remote operation of mobile robots. Also the differences between the application scenarios of mobile robot teams and in pure telecommunication environments are explained. The presented results are not only based on simulations. The ad-hoc routing protocols are compared in test scenarios with real mobile robot hardware experiments and the analysis is done according to well established methods and valid metrics well known from literature. Hints for the setup and parameter tuning of selected ad-hoc routing protocols are given to enable a better teleoperation of mobile robots and to improve the communication inside teams of mobile robots and humans. Finally a first approach is presented how to increase the system performance also on the application layer. Keywords: networked robots, tele-operations, mobile ad hoc networks, wireless, telematics. 1. INTRODUCTION In the last decades research in the field of robotics has produced impressive advances in many application areas, ranging from e.g. industrial manipulators, search and rescue, up to robots on Mars. Nevertheless, robots have still not found their place in everyday life. The reasons for this are manifold. In industry, robots are working in strictly defined environments and enable fast, reliable, and cheap production of high quality goods while they are operated by specially trained staff and depend on a fixed, defined infrastructure. But in other application areas (e.g. search and rescue), the environment is not completely defined. It underlies a lot of changes during the mission and robots cannot rely on existing infrastructure. Here, mobile robots can still not be applied efficiently and dependably, although their application in these fields would be very desirable. One key issue which still needs to be solved for such teams is the efficient and adaptable communication between the different entities involved. In the especially very challenging search and rescue example, it would be most desirable to have a group of mobile robots working together with humans, coordinated and supported by a human supervisor from outside the actual
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workspace. The communication for this type of humanrobot teams is crucial, but the different team members cannot rely on any existing infrastructure. Therefore, all involved entities have to provide and maintain their own communication infrastructure. In the early stages of teleoperating mobile robots, often a cable connection was used Birk and Condea (2006). Later, as the progress in the area of wireless communication brought up affordable devices, wireless connection between a dedicated control station and a mobile robot was common. With these technologies, no real integrated networks, like they are needed for the scenarios described before, were possible - only a direct link between mobile robot and control device was established. In nowadays scenarios really integrated networks where mobile robots are acting as data source, mobile actuator, or also as communication relay, are a must. Moreover, dynamic network topologies and any-to-any communication on a logical layer between each node of the network are important for a seamless integration of heterogeneous human-robot teams into the same communication network. Well tested technologies like IEEE 802.11 wireless LAN have a high potential to satisfy these needs. The availability of cheap and well tested equipment, as well as seamless integration into existing computer networks
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and the compatibility with existing communication devices like PDAs or mobile phones are major advantages of this technology. Wireless LAN also provides the possibility to realize ad-hoc networks with existing and standardized technologies. It allows realizing these networks of mobile robots and humans working as a team, where each entity can take over different roles in communication. Therefore, mechanisms for routing in ad-hoc networks (e.g. AODV, DSR, OLSR) were first developed in the area of telecommunication networks almost 10 years ago. Nowadays, more than 80 ad-hoc routing protocol designs exist, but only a few of them are implemented and ready to use. This work will give an overview on challenges and important parameters to realize the remote operation of mobile robots via wireless ad-hoc networks and it will report on experiences from using available ad-hoc routing protocols in mobile ad-hoc networks of robots. A set of implemented real-world experiments with networked robots using adhoc capabilities, and hints how to setup working ad-hoc networks in similar scenarios are presented. 2. WIRELESS AD-HOC NETWORKS AND MESH NETWORKS The term ad-hoc network refers to networks where interconnections between network nodes are set up in a spontaneous way. As a remarkable criterion for ad-hoc networks, there is no need for pre-configuration to enable direct communication between emerging adjacent nodes. Furthermore, within an ad-hoc network there is no central authority and no infrastructure that governs and routes information flow. As soon as adjacent network nodes manage to set up communication, the link is established and ready to use. Looking at wireless scenarios, it can clearly be recognized that interconnections within ad-hoc networks most times last only for a limited period of time. But in contrast to cutting existing links, mobility of nodes will also allow the introduction of new links. Communication might become possible between nodes that were out of reach only a short while ago. Although popular IEEE 802.11 wireless LAN is known for its use in managed infrastructure mode with central router devices, it is also supporting the ad-hoc mode since the very start. Not all participants of the network but only network nodes located within close proximity have the ability to exchange data between each other. Imagine three network nodes somehow arranged in a chain. The network node in the middle will be able to communicate to its two adjacent neighbors. But these two outer nodes might not be able to talk to each other because their distance exceeds the maximum range which has to be maintained in order to establish radio communication. As a result, this type of network can only give limited connectivity by plain means. Now, the idea of mesh networking comes into place. To get back to the simple example above, it is obvious that both outer nodes can communicate by means of a data relaying node in between. mesh networking introduces network nodes that in fact act as such relays, allowing data telegrams to ”hop” multiple nodes to reach the destination node. Performing a ”hop” means that a network node forwards a received telegram which is not intended for itself. It simply retransmits it to an adjacent node, choosing that node that will
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bring the telegram as near to its final destination as possible. For choosing the appropriate neighbor when forwarding data, routing tables are needed that guide the telegram through the network. By means of these routing and relaying mechanisms, connectivity within the mesh network dramatically increases compared to a simple adhoc network without relaying: ideally, all participants of the network will be able to communicate to all of each other by taking multiple hops. However, in practical use, the topology of a mesh network most times is not fixed. As already mentioned, mobility will affect and change network topology permanently. We will have to deal with mobile Ad-hoc Networks (MANETs). Nodes can join the network, move around or leave the network. Thus, the routes within the network often change and fixed routing tables are unfeasible. Further, the way routes will evolve often takes place in a quite unpredictable way - imagine wireless ad-hoc networks of large scale or highest mobility, where it is impractical or even impossible to predict connectivity. Of course, there is always the danger of spontaneous outages due to failing equipment, too. To overcome all these challenges, several algorithms have been developed that can discover and monitor network topology autonomously during runtime. They identify routes within a meshed network and respectively adapt routing on the fly. Thus, administration effort is minimized. Acting completely transparent, a robust network with connectivity at best is presented to the accessing users. Introducing this adaptive routing takes us one step further, from mesh networks to the class of mobile adhoc networks. The different algorithmic approaches to this problem will be presented and analyzed in the following sections. 3. TYPICAL SCENARIOS This section gives a brief overview of different communication approaches used in the area of mobile robots during the last years. The typical teleoperation scenario in the past aimed on simplicity and had the objective to guarantee reliable teleoperation of one mobile robot by a dedicated control station. The robot, as well as the control station use special equipment which provides a communication link only between these two entities and a further integration of additional network nodes is not foreseen. Examples for the successful application of this approach are given in Eck et al. (2007), where a rover is remotely controlled via a dedicated wireless link while navigating in an outdoor environment. In Musial et al. (2001) an autonomous unmanned helicopter is connected to the ground station via a dedicated link based on the DECT technology (ETSI-Standard EN300175). As described above, the wireless communication equipment is very sensitive to external influences and disturbances with respect to reliable transmission of data. Often, a direct line-of-sight is required to maintain the communication link. In case of extending the communication range also into areas which are in the communication shadow behind an obstacle, the use of communication relays is currently a common approach. In Pezeshkian et al. (2007), some communication relays are placed in case the link quality decreases, and thus, the range and reliability is increased. Nevertheless, the topology of the multi-hop network is de-
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Fig. 1. Scenario of humans and mobile robots integrated into a multi-hop network. cided in advance and configuration is done static before the stationary relay nodes are deployed. Thus, a later change of the topology is not foreseen and in this kind of setup a rerouting is not possible on demand. In case the stationary communication relays should be replaced by mobile nodes which can act either as active part of a mobile robot team or just as communication relay if necessary, dynamic topologies are coming into play. The capability of maintaining connectivity in a network with dynamic topology can be achieved by applying ad-hoc routing mechanisms. As already mentioned in the previous sections, there are many existing mechanisms acting according to different topology update principles. Reactive protocols are discovering routes on demand which reduces signaling traffic for rarely used routes to a minimum. Proactive mechanisms discover the network in advance and provide the routes to destinations immediately on request. This method creates some signaling traffic to maintain the routing tables and for spreading updates into the network in case of topology changes. In addition also hybrid approaches exist which try to combine the advantages of the formerly mentioned methods. Nevertheless, these mechanisms allow for scenarios which are displayed in Figure 1. The scenario shown in Figure 1 is based on a network which supports dynamic topologies and the integration of different network nodes (human, robots, sensors, stationary communication relays,...) by a common standard in combination with a transparent communication between all network nodes. This scenario is currently very interesting with respect to the application in the area of networked robotics as it supports one-to-one, one-to-many, many-to-one, and any-toany communication on a logical layer. This type of flexible communication which is transparent for the user is a must for nowadays networked robot scenarios where a seamless networking of all nodes is a prerequisite to accomplish a task successfully. Nevertheless, some challenges must be coped for a successful application of this technology in the field of networked robotics. In these scenarios usually video streams, sensor data, and commands to the robots are transmitted. Thus, a mixture of different types of traffic (delay sensitive, packet loss sensitive, real time,...). This might also require additional mechanisms on application layer like in Zeiger et al. (2008d), where a traffic shaping algorithm is presented. Also an appropriate parameter setting of the used protocols will increase the performance of the network and will enable the interconnection of
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Fig. 2. Test scenario for ad-hoc routing protocols. robots and humans via a common network. The following chapters will describe how these complex networks can be set up easily with standard WLAN equipment which is currently available. 4. TEST SETUP Figure 1 shows a scenario with a high grade of node mobility and a dynamic topology. Here, the network consists of stationary nodes, mobile robots (unmanned ground vehicles and unmanned aerial vehicles), and human team members. In addition to the previously mentioned scenario, several network nodes are mobile which requests the support of changing topologies. Inside the network each node competes for the medium access in its transmission range (cf. RFC IEEE 802.11). In Zeiger et al. (2008b) four ad-hoc routing protocols are analyzed with respect to mobile robot teleoperation. From the existing implementations of ad-hoc routing protocols, ”Ad-hoc On-demand Distance Vector” (AODV), ”Dynamic Source Routing” (DSR), ”Optimized Link State Routing” (OLSR), and ”Better Approach to Mobile Ad-Hoc Networking” (BATMAN) are selected for the tests. The test setup for this analysis is displayed in Figure 2 and represents a typical scenario from the area of robotics, especially for remote exploration tasks. Objective is the teleoperation and navigation of a mobile robot via wireless communication link. The communication infrastructure is set up on demand and in the test setup of Figure 2 an obstacle blocks a direct communication link to an area which should be explored by the robot. To provide seamless communication between the operator and the mobile robot, several nodes act as communication relays on-demand. The capability of using some nodes as communication relay is provided by the ad-hoc routing protocol which is analyzed. To allow for a characterization of the ad-hoc routing protocols for mobile robot teleoperation applications, the analysis of the duration for the rerouting is important. Also, the packet loss and the behavior of the routing protocols while handling worst-case topologies like shown in Figure 2 with unstable links are of interest. In a first step, the routing protocols are used with standard parameter settings and the round trip time (rtt) of packets, the packet loss and the duration of the rerouting procedure is analyzed in this scenario. These initial tests are described in Zeiger et al. (2008b) and results of representative test runs are
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shown in Figure 3. The measured rtt is plotted over the experiment time (tex ) whereas the y-axis represents the rtt in milliseconds and the x-axis represents tex in seconds. At the bottom of the graphs, the numbers of the hops which are used for the communication link are given. Figure 3a shows the results of the behavior of BATMAN with default parameter settings in the above described scenario. Until approximately tex =50 seconds, the mobile robot is controlled via a direct line-of-sight connection and no relay node is used. After losing the direct line-of-sight, the connection is lost and could not be reestablished by the BATMAN routing protocol. In Figure 3b, the behavior of AODV is depicted. It can be seen that several communication losses occurred during the test run. Between approximately tex =28 seconds and tex =32 seconds the direct communication between control station and mobile robot is lost as the communication range is left after moving the robot around the obstacle. AODV now initiates a route reestablishing which provides a new communication link via one relay node at tex =32 seconds. While communicating via the relay, several relatively long communication link losses happened when the robot looses the direct lineof-sight to the previously connected communication node again (cf. Figure 3b) at about tex =54 seconds). Zeiger et al. (2008b) also investigated DSR and OLSR which performed still not satisfactory. Also OLSR showed an unsatisfying behavior with the default parameter setting. After detecting a link failure, the ad-hoc routing protocols initiate a route reestablishing procedure and it takes some time until the communication link is up and running again. The duration of these interrupts depend on the functioning of the corresponding ad-hoc routing protocol, and of course it is also influenced by the environmental conditions and the link quality. Some of these interrupts last too long, so that the teleoperation performance is decreased significantly. More details on these tests are given in Zeiger et al. (2008b). As the measured performance of the used ad-hoc protocols did not satisfy the expectations, these results lead to the conclusion to observe the effects of changing the ad-hoc routing protocol parameter settings in order to improve the performance.
(a) BATMAN
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Fig. 3. Default parameter settings. In Zeiger et al. (2008a), the parameter tuning with respect to mobile robot teleoperation of the four above mentioned routing protocols is analyzed in detail. Of course, as the protocols have different working principles, also the type of parameters and the behavior of the protocols differ. The results of the test runs with tuned parameters are
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presented in Figure 4. Again, the y-axis presents the measured round trip time in milliseconds, the x-axis shows the experiment time in seconds, and the number of used hops is shown at the bottom of the graph. Compared to the results of the tests with default parameter settings, better results are achieved due to the parameter adjustments of the protocols. In Figure 4a, the performance of BATMAN is shown and it can be observed that the maximum duration of a communication drop out is much smaller than experienced during the tests for the standard parameter settings. Figure 4b shows the results of AODV with tuned parameters. The initiation of the first hop between tex =35 and tex =50 seconds was not successful immediately. Here, the AODV reestablished the communication link via two hops. Nevertheless, the rerouting with tuned parameters showed a better performance than the rerouting with default parameters. More details on the tests and evaluation of BATMAN, AODV, DSR, and OLSR for this setup are given in Zeiger et al. (2008a).
(a) BATMAN
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Fig. 4. Tuned parameter settings. These results raised a further question compared to results which are published in related work in the field of telecommunication, as the measurements presented above differ significantly from results published in the past. The work of Perkins et al. (2001) and Broch et al. (1998) investigated the performance of important ad-hoc routing protocols (AODV and DSR amongst others) in a simulation study. In contrast to the presented real-world applications, these simulations have shown a much better performance of the used protocols than observed during the real-world tests with the mobile robots (cf. Zeiger et al. (2008a)). One reason for this result is, that the used test setup is not identical compared to the scenarios of the simulations in Perkins et al. (2001) and Broch et al. (1998). The above presented network with mobile robots has a very low grade of meshing and the mission of the mobile robot will inescapably lead to the extreme situation of a ”chain” of relay nodes to keep the mobile robot connected to the control PC. In this case, no redundant routes are present and only one communication link is possible. This might lead to further complications as e.g. AODV is using a black-listing mechanism for unstable links and in case the protocol detects an unstable link, this link will be added to the blacklist and cannot be used for the next minutes - even if this is the only possible connection. A second reason for the observed differences is the testing with real hardware in a real world scenario. Zeiger et al. (2008c) discussed several challenges for the setup and evaluation of real world tests of ad-hoc networks with mobile robots.
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Fig. 5. Frame rate and transmitted data. Zeiger et al. (2008d) proposed a mechanism to minimize packet loss and communication drop-outs by shaping the transmitted traffic using the example of video transmission. The aim of the mechanism is an admission control of a data source taking into account the current state of the used links inside the network. Thus, the available bandwidth can be used efficiently without overloading the route which is also used for data transport. To reach these objectives, two main components are used: the network feedback, and the adaptive adjustment of the video quality. The network feedback is generated by a network feedback client running on dedicated nodes inside the network (not all nodes have to provide this service - cf. Zeiger et al. (2008d)). This client program is listening for all kind of data in promiscuous mode at layer 3 of the ISO/OSI model (IP-layer) and measures the utilization of the wireless link. The link utilization then can be calculated by taking into account the current nominal bandwidth available, which might vary between 1 and 54 Mbits/sec due to link quality changes. The interpretation of the measured link utilization (”normal operation” or ”overload situation”) is done by using a given threshold value applied to the nominal available bandwidth. As soon as the link utilization exceeds this threshold, an overload
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In the previous section it was shown that parameter tuning of the ad-hoc routing protocol is required to practically realize an ad-hoc network for mobile robots. Also, some hints for the selection of a protocol with respect to the scenario is given. This section will show how on the other hand the traffic generated on the application layer can be shaped in order to increase the performance of the adhoc routing protocols. This means to shape the generated traffic in order to reserve enough bandwidth on the links, such that the protocols can update the routing tables quickly according to the changing scenario and bandwidth utilization. A typical example scenario is the teleoperation of a mobile robot over multiple hops. Here, in addition to the protocol parameter tuning, the traffic shaping is very essential. For teleoperation the video received from the remote environment is still the most important feedback to increase the situational awareness of the human operator. On the other hand this video data has high bandwidth requirements on the communication link, and herby can also significantly disturb the whole communication. This is especially the case if it is used inside a WLAN adhoc network. Different typical situations can occur which causes significant communication problems like packet loss or even a complete connection loss. First, the nominal bandwidth of one of the links in the multi-hop connection is reduced due to decreasing signal strength influenced by environmental conditions or simply a changed distance between the two communicating nodes. Second, one of the nodes in the communication chain has to handle additional traffic for a different connection where it is also
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a relay node for a multi-hop connection. If the available bandwidth for the communication link decreases and the application is not also limiting the transmitted data, an overload situation with packet loss occurs, and also the necessary signal packets of the ad-hoc routing protocols cannot be transmitted properly anymore. These effects are even more crucial due to the half-duplex characteristics of WLAN. Figure 5a shows a typical plot from an experiment with real robots, where a video stream is send from a mobile robot to a human operator via one intermediate node using an ad-hoc routing protocol (BATMAN). Here, the received frame rate of a transmitted video stream is shown. This frame rate is used as the crucial quality parameter for mobile robot teleoperation and behaves inverse proportional to the packet loss on the link. After approximately 60 seconds an additional, constant traffic was send over the intermediate node, what causes a significant packet loss, and hereby an instable, decreased frame rate and decreased data throughput of the link can be observed. In this overload situation a human operator would stop the mobile robot immediately and wait for a recovery of the frame rate, because he/she cannot reason safely about the remote situation anymore. In order to avoid this, a careful monitoring of the used route of an established multi-hop connection and adaptation of the generated traffic to the current situation is needed.
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Issues like the definition of meaningful test setups according to the needs of the robotics application, repeatability and comparability of test runs, and the variability of disturbances must be considered in order to get satisfactory results. Nevertheless, the presented work shows that existing ad-hoc routing protocols for mobile robot teleoperation are applicable if the protocol parameters are tuned according to the scenario and the mission which should be accomplished. The scenario which is used in this work represents a worst-case scenario in the means of redundant routes. Also here, it is possible to increase the teleoperation capabilities of the mobile robots by an appropriate tuning of the parameters of the routing protocols. Of course, also the mission or the scenario itself is an important selection criterion for the decision which ad-hoc routing protocol should be used. In the presented scenario, where the relay nodes are positioned in line (low grade of meshing, no redundant routes), the use of ad-hoc routing protocols which support the blacklisting of unstable links (e.g. AODV) is not a good choice. In this case DSR and BATMAN with tuned parameters perform better. In case the node topology has a high grade of meshing (redundant routes are available) AODV is performing better and can be used. In Zeiger et al. (2008a) and Zeiger et al. (2008b), the performance of DSR was always quite acceptable which makes this a good choice for application scenarios where the expected topology is unknown. Enabling mobile robot teleoperation in the described scenario offers the opportunity for several interesting and promising applications in the area of networked robotics, and some of them are described in the following section.
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situation is indicated. The measured status information is the sent to the data source with an adjustable frequency. The behavior of the feedback mechanism is determined by the feedback frequency and the threshold for status determination. The video quality adaptation mechanism is responsible for selecting the appropriate quality of the video frames according to the network status. Therefore, network feedback packets of the nodes are received and interpreted by the node transmitting the video. By reducing the image quality also the amount of generated traffic is reduced and hereby also the link utilization. Fig. 5b shows the result of the experiment with the setup explained before but now with the implemented traffic shaping mechanism. The results prove, that the adaptation of the generated traffic according to the current network status makes it possible to keep the frame rate in the desired interval (here: approx. 11 frames per second). Zeiger et al. (2008d) presents this traffic shaping mechanism and investigates its behavior with respect to video transmission via a multi-hop network for an exploration and navigation task. Other applications and types of traffic might require an even more careful monitoring of to the current network status and respective reactions on the changes. Interesting examples are scenarios where the human operator reacts instantaneously on feedback from the robot without having an intuitive feedback about communication problems (e.g. stumbling video). For instance, if sensor feedback from the mobile robot is used to generate a haptic feedback for the human in order to guide him/her around obstacles Lee et al. (2005), significantly varying delays or packet loss might lead to a haptic feedback for the operator, which is not representing the current situation in the remote environment. Thus, the human operator will generate commands based on wrong information. Other examples are distributed control algorithms for coordination of group of mobile robots. Here, also the robustness and stability depend very much on the jitter, delay, and drop-outs of the communication. Therefore, these types of applications require a careful design on all system levels (tuning of protocol parameters and the selection of protocol, traffic generation on application layer, usage of transmitted data in the algorithms) to successfully enable mobile robots to be teleoperated via ad-hoc networks. 6. CONCLUSION To realize the teleoperation of mobile robots and the integration of robots into teams of humans and robots, a transparent and reliable communication is necessary. Therefore, the required communication mechanisms must enable dynamic network topologies and the mobility of the several network nodes. This article is discussing the possibilities of integrating mobile robots into heterogeneous teams and the communication of the nodes via ad-hoc networks. Also the realization of mobile robot teleoperation via ad-hoc networks, and recommendations of how to use existing adhoc routing protocol implementations in typical networked mobile robot scenarios are presented. Unfortunately, the default parameter settings of the available ad-hoc routing protocols lead to unsatisfying results and thus, modifications of the parameter settings are presented in order to achieve a suitable performance. Additionally, guidelines for the definition, setup, and evaluation of test scenarios for the application of wireless LAN ad-hoc networks for
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mobile robots are given. Also the assets and drawbacks of the several ad-hoc routing protocols with respect to the scenarios are discussed. Finally, some future prospects of applications in the area of mobile robot teleoperation and networked robots are given - e.g. the traffic shaping mechanism based on network feedback which can be used in wireless ad-hoc networks. It could be shown how existing communication technologies (e.g. WLAN) could be used to integrate heterogeneous teams of humans and mobile robots successfully. REFERENCES Birk, A. and Condea, C. (2006). Mobile robot communication without the drawbacks of wireless networking. In I. Noda, A. Jacoff, A. Bredenfeld, and Y. Takahashi (eds.), RoboCup 2005: Robot Soccer World Cup IX, volume 4020 of Lecture Notes in Artificial Intelligence (LNAI), 585 – 592. Springer. Broch, J., Maltz, D.A., Johnson, D.B., Hu, Y.C., and Jetcheva, J. (1998). A performance comparison of multihop wireless ad hoc network routing protocols. In Mobile Computing and Networking, 85–97. Eck, D., Stahl, M., and Schilling, K. (2007). The Small Outdoor Rover MERLIN and its Assistance System for Tele-Operations. In Proc. of Int. Conf. on Field and Service Robotics, Chamonix, France. Lee, S., Sukhatme, G.S., Kim, G.J., and Park, C.M. (2005). Haptic teleoperation of a mobile robot: A user study. Presence: Teleoperators & Virtual Environments, 14(3), 345–365. Musial, M., Brandenburg, U.W., and Hommel, G. (2001). Success of an Inexpensive System Design: The Flying Robot MARVIN. In 16th Int. Unmanned Air Vehicle System Conf. (UAVs). Perkins, C., Royer, E., Das, S., and Marina, M. (2001). Performance comparison of two on-demand routing protocols for ad hoc networks. IEEE Personal Communications, 8(1), 16–28. Pezeshkian, N., Nguyen, H.G., and Burmeister, A. (2007). Unmanned ground vehicle radio relay deployment system for non-line-of-sight operations. In Proc. of the 13th IASTED Int. Conf. on Robotics and Applications, August 29-31, W¨ urzburg, Germany, RA2007. Zeiger, F., Kraemer, N., and Schilling, K. (2008a). Parameter tuning of routing protocols to improve the performance of mobile robot teleoperation via wireless ad-hoc networks. In 5th International Conference on Informatics, Automation and Robotics (ICINCO 2008). Zeiger, F., Kr¨amer, N., and Schilling, K. (2008b). Commanding mobile robots via wireless ad-hoc networks - a comparison of four ad-hoc routing protocol implementations. In IEEE Int. Conf. on Robotics and Automation (ICRA 2008). Zeiger, F., Krmer, N., Sauer, M., and Schilling, K. (2008c). Challenges in Realizing Ad-Hoc Networks based on Wireless LAN with Mobile Robots. In Workshop on Wireless Multihop Communications in Networked Robotics (WMCNR 2008). Zeiger, F., Sauer, M., and Schilling;, K. (2008d). Video Transmission with Adaptive Quality based on Network Feedback for Mobile Robot Teleoperation in Wireless Multi-Hop Networks. In 5th Int. Conf. on Informatics, Automation and Robotics (ICINCO 2008).
Integrating Teams of Mobile Robots in Wireless Ad-Hoc Networks Florian Zeiger ∗ Markus Sauer ∗ Lothar Stolz ∗ Klaus Schilling ∗∗ Center for Telematics, W¨ urzburg , Germany (e-mail: {florian.zeiger,markus.sauer,lothar.stolz}@telematik-zentrum.de). ∗∗ Department of Computer Science - Robotics and Telematics, University of W¨ urzburg, W¨ urzburg , Germany (e-mail: {schi}@informatik.uni-wuerzburg.de). ∗
Abstract: Modern applications of mobile robot teams or robot teleoperation often demand wireless any-to-any communication in combination with highly dynamical network topologies to accomplish more and more complex tasks. These communication systems should also not rely on any pre-existing infrastructure, have low costs, and should allow for a seamless integration into existing communication networks. The well tested technology IEEE 802.11 wireless LAN offers all these possibilities. Especially the capability of realizing ad-hoc networks offers a high potential for WLAN to be used in the area of networked robots. Mesh networks and mobile ad-hoc networks are able to provide mechanisms for realizing stable communication links for networked robots. This work gives a brief overview on mesh networks and ad-hoc networks and further shows the behavior of different ad-hoc routing protocols (AODV, OLSR, DSR, BATMAN) in typical scenarios for remote operation of mobile robots. Also the differences between the application scenarios of mobile robot teams and in pure telecommunication environments are explained. The presented results are not only based on simulations. The ad-hoc routing protocols are compared in test scenarios with real mobile robot hardware experiments and the analysis is done according to well established methods and valid metrics well known from literature. Hints for the setup and parameter tuning of selected ad-hoc routing protocols are given to enable a better teleoperation of mobile robots and to improve the communication inside teams of mobile robots and humans. Finally a first approach is presented how to increase the system performance also on the application layer. Keywords: networked robots, tele-operations, mobile ad hoc networks, wireless, telematics. 1. INTRODUCTION In the last decades research in the field of robotics has produced impressive advances in many application areas, ranging from e.g. industrial manipulators, search and rescue, up to robots on Mars. Nevertheless, robots have still not found their place in everyday life. The reasons for this are manifold. In industry, robots are working in strictly defined environments and enable fast, reliable, and cheap production of high quality goods while they are operated by specially trained staff and depend on a fixed, defined infrastructure. But in other application areas (e.g. search and rescue), the environment is not completely defined. It underlies a lot of changes during the mission and robots cannot rely on existing infrastructure. Here, mobile robots can still not be applied efficiently and dependably, although their application in these fields would be very desirable. One key issue which still needs to be solved for such teams is the efficient and adaptable communication between the different entities involved. In the especially very challenging search and rescue example, it would be most desirable to have a group of mobile robots working together with humans, coordinated and supported by a human supervisor from outside the actual
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workspace. The communication for this type of humanrobot teams is crucial, but the different team members cannot rely on any existing infrastructure. Therefore, all involved entities have to provide and maintain their own communication infrastructure. In the early stages of teleoperating mobile robots, often a cable connection was used Birk and Condea (2006). Later, as the progress in the area of wireless communication brought up affordable devices, wireless connection between a dedicated control station and a mobile robot was common. With these technologies, no real integrated networks, like they are needed for the scenarios described before, were possible - only a direct link between mobile robot and control device was established. In nowadays scenarios really integrated networks where mobile robots are acting as data source, mobile actuator, or also as communication relay, are a must. Moreover, dynamic network topologies and any-to-any communication on a logical layer between each node of the network are important for a seamless integration of heterogeneous human-robot teams into the same communication network. Well tested technologies like IEEE 802.11 wireless LAN have a high potential to satisfy these needs. The availability of cheap and well tested equipment, as well as seamless integration into existing computer networks
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IFAC NetRob 2009 Golden, CO, USA, October 6-8, 2009
and the compatibility with existing communication devices like PDAs or mobile phones are major advantages of this technology. Wireless LAN also provides the possibility to realize ad-hoc networks with existing and standardized technologies. It allows realizing these networks of mobile robots and humans working as a team, where each entity can take over different roles in communication. Therefore, mechanisms for routing in ad-hoc networks (e.g. AODV, DSR, OLSR) were first developed in the area of telecommunication networks almost 10 years ago. Nowadays, more than 80 ad-hoc routing protocol designs exist, but only a few of them are implemented and ready to use. This work will give an overview on challenges and important parameters to realize the remote operation of mobile robots via wireless ad-hoc networks and it will report on experiences from using available ad-hoc routing protocols in mobile ad-hoc networks of robots. A set of implemented real-world experiments with networked robots using adhoc capabilities, and hints how to setup working ad-hoc networks in similar scenarios are presented. 2. WIRELESS AD-HOC NETWORKS AND MESH NETWORKS The term ad-hoc network refers to networks where interconnections between network nodes are set up in a spontaneous way. As a remarkable criterion for ad-hoc networks, there is no need for pre-configuration to enable direct communication between emerging adjacent nodes. Furthermore, within an ad-hoc network there is no central authority and no infrastructure that governs and routes information flow. As soon as adjacent network nodes manage to set up communication, the link is established and ready to use. Looking at wireless scenarios, it can clearly be recognized that interconnections within ad-hoc networks most times last only for a limited period of time. But in contrast to cutting existing links, mobility of nodes will also allow the introduction of new links. Communication might become possible between nodes that were out of reach only a short while ago. Although popular IEEE 802.11 wireless LAN is known for its use in managed infrastructure mode with central router devices, it is also supporting the ad-hoc mode since the very start. Not all participants of the network but only network nodes located within close proximity have the ability to exchange data between each other. Imagine three network nodes somehow arranged in a chain. The network node in the middle will be able to communicate to its two adjacent neighbors. But these two outer nodes might not be able to talk to each other because their distance exceeds the maximum range which has to be maintained in order to establish radio communication. As a result, this type of network can only give limited connectivity by plain means. Now, the idea of mesh networking comes into place. To get back to the simple example above, it is obvious that both outer nodes can communicate by means of a data relaying node in between. mesh networking introduces network nodes that in fact act as such relays, allowing data telegrams to ”hop” multiple nodes to reach the destination node. Performing a ”hop” means that a network node forwards a received telegram which is not intended for itself. It simply retransmits it to an adjacent node, choosing that node that will
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bring the telegram as near to its final destination as possible. For choosing the appropriate neighbor when forwarding data, routing tables are needed that guide the telegram through the network. By means of these routing and relaying mechanisms, connectivity within the mesh network dramatically increases compared to a simple adhoc network without relaying: ideally, all participants of the network will be able to communicate to all of each other by taking multiple hops. However, in practical use, the topology of a mesh network most times is not fixed. As already mentioned, mobility will affect and change network topology permanently. We will have to deal with mobile Ad-hoc Networks (MANETs). Nodes can join the network, move around or leave the network. Thus, the routes within the network often change and fixed routing tables are unfeasible. Further, the way routes will evolve often takes place in a quite unpredictable way - imagine wireless ad-hoc networks of large scale or highest mobility, where it is impractical or even impossible to predict connectivity. Of course, there is always the danger of spontaneous outages due to failing equipment, too. To overcome all these challenges, several algorithms have been developed that can discover and monitor network topology autonomously during runtime. They identify routes within a meshed network and respectively adapt routing on the fly. Thus, administration effort is minimized. Acting completely transparent, a robust network with connectivity at best is presented to the accessing users. Introducing this adaptive routing takes us one step further, from mesh networks to the class of mobile adhoc networks. The different algorithmic approaches to this problem will be presented and analyzed in the following sections. 3. TYPICAL SCENARIOS This section gives a brief overview of different communication approaches used in the area of mobile robots during the last years. The typical teleoperation scenario in the past aimed on simplicity and had the objective to guarantee reliable teleoperation of one mobile robot by a dedicated control station. The robot, as well as the control station use special equipment which provides a communication link only between these two entities and a further integration of additional network nodes is not foreseen. Examples for the successful application of this approach are given in Eck et al. (2007), where a rover is remotely controlled via a dedicated wireless link while navigating in an outdoor environment. In Musial et al. (2001) an autonomous unmanned helicopter is connected to the ground station via a dedicated link based on the DECT technology (ETSI-Standard EN300175). As described above, the wireless communication equipment is very sensitive to external influences and disturbances with respect to reliable transmission of data. Often, a direct line-of-sight is required to maintain the communication link. In case of extending the communication range also into areas which are in the communication shadow behind an obstacle, the use of communication relays is currently a common approach. In Pezeshkian et al. (2007), some communication relays are placed in case the link quality decreases, and thus, the range and reliability is increased. Nevertheless, the topology of the multi-hop network is de-
IFAC NetRob 2009 Golden, CO, USA, October 6-8, 2009
Fig. 1. Scenario of humans and mobile robots integrated into a multi-hop network. cided in advance and configuration is done static before the stationary relay nodes are deployed. Thus, a later change of the topology is not foreseen and in this kind of setup a rerouting is not possible on demand. In case the stationary communication relays should be replaced by mobile nodes which can act either as active part of a mobile robot team or just as communication relay if necessary, dynamic topologies are coming into play. The capability of maintaining connectivity in a network with dynamic topology can be achieved by applying ad-hoc routing mechanisms. As already mentioned in the previous sections, there are many existing mechanisms acting according to different topology update principles. Reactive protocols are discovering routes on demand which reduces signaling traffic for rarely used routes to a minimum. Proactive mechanisms discover the network in advance and provide the routes to destinations immediately on request. This method creates some signaling traffic to maintain the routing tables and for spreading updates into the network in case of topology changes. In addition also hybrid approaches exist which try to combine the advantages of the formerly mentioned methods. Nevertheless, these mechanisms allow for scenarios which are displayed in Figure 1. The scenario shown in Figure 1 is based on a network which supports dynamic topologies and the integration of different network nodes (human, robots, sensors, stationary communication relays,...) by a common standard in combination with a transparent communication between all network nodes. This scenario is currently very interesting with respect to the application in the area of networked robotics as it supports one-to-one, one-to-many, many-to-one, and any-toany communication on a logical layer. This type of flexible communication which is transparent for the user is a must for nowadays networked robot scenarios where a seamless networking of all nodes is a prerequisite to accomplish a task successfully. Nevertheless, some challenges must be coped for a successful application of this technology in the field of networked robotics. In these scenarios usually video streams, sensor data, and commands to the robots are transmitted. Thus, a mixture of different types of traffic (delay sensitive, packet loss sensitive, real time,...). This might also require additional mechanisms on application layer like in Zeiger et al. (2008d), where a traffic shaping algorithm is presented. Also an appropriate parameter setting of the used protocols will increase the performance of the network and will enable the interconnection of
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Fig. 2. Test scenario for ad-hoc routing protocols. robots and humans via a common network. The following chapters will describe how these complex networks can be set up easily with standard WLAN equipment which is currently available. 4. TEST SETUP Figure 1 shows a scenario with a high grade of node mobility and a dynamic topology. Here, the network consists of stationary nodes, mobile robots (unmanned ground vehicles and unmanned aerial vehicles), and human team members. In addition to the previously mentioned scenario, several network nodes are mobile which requests the support of changing topologies. Inside the network each node competes for the medium access in its transmission range (cf. RFC IEEE 802.11). In Zeiger et al. (2008b) four ad-hoc routing protocols are analyzed with respect to mobile robot teleoperation. From the existing implementations of ad-hoc routing protocols, ”Ad-hoc On-demand Distance Vector” (AODV), ”Dynamic Source Routing” (DSR), ”Optimized Link State Routing” (OLSR), and ”Better Approach to Mobile Ad-Hoc Networking” (BATMAN) are selected for the tests. The test setup for this analysis is displayed in Figure 2 and represents a typical scenario from the area of robotics, especially for remote exploration tasks. Objective is the teleoperation and navigation of a mobile robot via wireless communication link. The communication infrastructure is set up on demand and in the test setup of Figure 2 an obstacle blocks a direct communication link to an area which should be explored by the robot. To provide seamless communication between the operator and the mobile robot, several nodes act as communication relays on-demand. The capability of using some nodes as communication relay is provided by the ad-hoc routing protocol which is analyzed. To allow for a characterization of the ad-hoc routing protocols for mobile robot teleoperation applications, the analysis of the duration for the rerouting is important. Also, the packet loss and the behavior of the routing protocols while handling worst-case topologies like shown in Figure 2 with unstable links are of interest. In a first step, the routing protocols are used with standard parameter settings and the round trip time (rtt) of packets, the packet loss and the duration of the rerouting procedure is analyzed in this scenario. These initial tests are described in Zeiger et al. (2008b) and results of representative test runs are
IFAC NetRob 2009 Golden, CO, USA, October 6-8, 2009
shown in Figure 3. The measured rtt is plotted over the experiment time (tex ) whereas the y-axis represents the rtt in milliseconds and the x-axis represents tex in seconds. At the bottom of the graphs, the numbers of the hops which are used for the communication link are given. Figure 3a shows the results of the behavior of BATMAN with default parameter settings in the above described scenario. Until approximately tex =50 seconds, the mobile robot is controlled via a direct line-of-sight connection and no relay node is used. After losing the direct line-of-sight, the connection is lost and could not be reestablished by the BATMAN routing protocol. In Figure 3b, the behavior of AODV is depicted. It can be seen that several communication losses occurred during the test run. Between approximately tex =28 seconds and tex =32 seconds the direct communication between control station and mobile robot is lost as the communication range is left after moving the robot around the obstacle. AODV now initiates a route reestablishing which provides a new communication link via one relay node at tex =32 seconds. While communicating via the relay, several relatively long communication link losses happened when the robot looses the direct lineof-sight to the previously connected communication node again (cf. Figure 3b) at about tex =54 seconds). Zeiger et al. (2008b) also investigated DSR and OLSR which performed still not satisfactory. Also OLSR showed an unsatisfying behavior with the default parameter setting. After detecting a link failure, the ad-hoc routing protocols initiate a route reestablishing procedure and it takes some time until the communication link is up and running again. The duration of these interrupts depend on the functioning of the corresponding ad-hoc routing protocol, and of course it is also influenced by the environmental conditions and the link quality. Some of these interrupts last too long, so that the teleoperation performance is decreased significantly. More details on these tests are given in Zeiger et al. (2008b). As the measured performance of the used ad-hoc protocols did not satisfy the expectations, these results lead to the conclusion to observe the effects of changing the ad-hoc routing protocol parameter settings in order to improve the performance.
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Fig. 3. Default parameter settings. In Zeiger et al. (2008a), the parameter tuning with respect to mobile robot teleoperation of the four above mentioned routing protocols is analyzed in detail. Of course, as the protocols have different working principles, also the type of parameters and the behavior of the protocols differ. The results of the test runs with tuned parameters are
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presented in Figure 4. Again, the y-axis presents the measured round trip time in milliseconds, the x-axis shows the experiment time in seconds, and the number of used hops is shown at the bottom of the graph. Compared to the results of the tests with default parameter settings, better results are achieved due to the parameter adjustments of the protocols. In Figure 4a, the performance of BATMAN is shown and it can be observed that the maximum duration of a communication drop out is much smaller than experienced during the tests for the standard parameter settings. Figure 4b shows the results of AODV with tuned parameters. The initiation of the first hop between tex =35 and tex =50 seconds was not successful immediately. Here, the AODV reestablished the communication link via two hops. Nevertheless, the rerouting with tuned parameters showed a better performance than the rerouting with default parameters. More details on the tests and evaluation of BATMAN, AODV, DSR, and OLSR for this setup are given in Zeiger et al. (2008a).
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Fig. 4. Tuned parameter settings. These results raised a further question compared to results which are published in related work in the field of telecommunication, as the measurements presented above differ significantly from results published in the past. The work of Perkins et al. (2001) and Broch et al. (1998) investigated the performance of important ad-hoc routing protocols (AODV and DSR amongst others) in a simulation study. In contrast to the presented real-world applications, these simulations have shown a much better performance of the used protocols than observed during the real-world tests with the mobile robots (cf. Zeiger et al. (2008a)). One reason for this result is, that the used test setup is not identical compared to the scenarios of the simulations in Perkins et al. (2001) and Broch et al. (1998). The above presented network with mobile robots has a very low grade of meshing and the mission of the mobile robot will inescapably lead to the extreme situation of a ”chain” of relay nodes to keep the mobile robot connected to the control PC. In this case, no redundant routes are present and only one communication link is possible. This might lead to further complications as e.g. AODV is using a black-listing mechanism for unstable links and in case the protocol detects an unstable link, this link will be added to the blacklist and cannot be used for the next minutes - even if this is the only possible connection. A second reason for the observed differences is the testing with real hardware in a real world scenario. Zeiger et al. (2008c) discussed several challenges for the setup and evaluation of real world tests of ad-hoc networks with mobile robots.
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In the previous section it was shown that parameter tuning of the ad-hoc routing protocol is required to practically realize an ad-hoc network for mobile robots. Also, some hints for the selection of a protocol with respect to the scenario is given. This section will show how on the other hand the traffic generated on the application layer can be shaped in order to increase the performance of the adhoc routing protocols. This means to shape the generated traffic in order to reserve enough bandwidth on the links, such that the protocols can update the routing tables quickly according to the changing scenario and bandwidth utilization. A typical example scenario is the teleoperation of a mobile robot over multiple hops. Here, in addition to the protocol parameter tuning, the traffic shaping is very essential. For teleoperation the video received from the remote environment is still the most important feedback to increase the situational awareness of the human operator. On the other hand this video data has high bandwidth requirements on the communication link, and herby can also significantly disturb the whole communication. This is especially the case if it is used inside a WLAN adhoc network. Different typical situations can occur which causes significant communication problems like packet loss or even a complete connection loss. First, the nominal bandwidth of one of the links in the multi-hop connection is reduced due to decreasing signal strength influenced by environmental conditions or simply a changed distance between the two communicating nodes. Second, one of the nodes in the communication chain has to handle additional traffic for a different connection where it is also
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a relay node for a multi-hop connection. If the available bandwidth for the communication link decreases and the application is not also limiting the transmitted data, an overload situation with packet loss occurs, and also the necessary signal packets of the ad-hoc routing protocols cannot be transmitted properly anymore. These effects are even more crucial due to the half-duplex characteristics of WLAN. Figure 5a shows a typical plot from an experiment with real robots, where a video stream is send from a mobile robot to a human operator via one intermediate node using an ad-hoc routing protocol (BATMAN). Here, the received frame rate of a transmitted video stream is shown. This frame rate is used as the crucial quality parameter for mobile robot teleoperation and behaves inverse proportional to the packet loss on the link. After approximately 60 seconds an additional, constant traffic was send over the intermediate node, what causes a significant packet loss, and hereby an instable, decreased frame rate and decreased data throughput of the link can be observed. In this overload situation a human operator would stop the mobile robot immediately and wait for a recovery of the frame rate, because he/she cannot reason safely about the remote situation anymore. In order to avoid this, a careful monitoring of the used route of an established multi-hop connection and adaptation of the generated traffic to the current situation is needed.
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Issues like the definition of meaningful test setups according to the needs of the robotics application, repeatability and comparability of test runs, and the variability of disturbances must be considered in order to get satisfactory results. Nevertheless, the presented work shows that existing ad-hoc routing protocols for mobile robot teleoperation are applicable if the protocol parameters are tuned according to the scenario and the mission which should be accomplished. The scenario which is used in this work represents a worst-case scenario in the means of redundant routes. Also here, it is possible to increase the teleoperation capabilities of the mobile robots by an appropriate tuning of the parameters of the routing protocols. Of course, also the mission or the scenario itself is an important selection criterion for the decision which ad-hoc routing protocol should be used. In the presented scenario, where the relay nodes are positioned in line (low grade of meshing, no redundant routes), the use of ad-hoc routing protocols which support the blacklisting of unstable links (e.g. AODV) is not a good choice. In this case DSR and BATMAN with tuned parameters perform better. In case the node topology has a high grade of meshing (redundant routes are available) AODV is performing better and can be used. In Zeiger et al. (2008a) and Zeiger et al. (2008b), the performance of DSR was always quite acceptable which makes this a good choice for application scenarios where the expected topology is unknown. Enabling mobile robot teleoperation in the described scenario offers the opportunity for several interesting and promising applications in the area of networked robotics, and some of them are described in the following section.
IFAC NetRob 2009 Golden, CO, USA, October 6-8, 2009
situation is indicated. The measured status information is the sent to the data source with an adjustable frequency. The behavior of the feedback mechanism is determined by the feedback frequency and the threshold for status determination. The video quality adaptation mechanism is responsible for selecting the appropriate quality of the video frames according to the network status. Therefore, network feedback packets of the nodes are received and interpreted by the node transmitting the video. By reducing the image quality also the amount of generated traffic is reduced and hereby also the link utilization. Fig. 5b shows the result of the experiment with the setup explained before but now with the implemented traffic shaping mechanism. The results prove, that the adaptation of the generated traffic according to the current network status makes it possible to keep the frame rate in the desired interval (here: approx. 11 frames per second). Zeiger et al. (2008d) presents this traffic shaping mechanism and investigates its behavior with respect to video transmission via a multi-hop network for an exploration and navigation task. Other applications and types of traffic might require an even more careful monitoring of to the current network status and respective reactions on the changes. Interesting examples are scenarios where the human operator reacts instantaneously on feedback from the robot without having an intuitive feedback about communication problems (e.g. stumbling video). For instance, if sensor feedback from the mobile robot is used to generate a haptic feedback for the human in order to guide him/her around obstacles Lee et al. (2005), significantly varying delays or packet loss might lead to a haptic feedback for the operator, which is not representing the current situation in the remote environment. Thus, the human operator will generate commands based on wrong information. Other examples are distributed control algorithms for coordination of group of mobile robots. Here, also the robustness and stability depend very much on the jitter, delay, and drop-outs of the communication. Therefore, these types of applications require a careful design on all system levels (tuning of protocol parameters and the selection of protocol, traffic generation on application layer, usage of transmitted data in the algorithms) to successfully enable mobile robots to be teleoperated via ad-hoc networks. 6. CONCLUSION To realize the teleoperation of mobile robots and the integration of robots into teams of humans and robots, a transparent and reliable communication is necessary. Therefore, the required communication mechanisms must enable dynamic network topologies and the mobility of the several network nodes. This article is discussing the possibilities of integrating mobile robots into heterogeneous teams and the communication of the nodes via ad-hoc networks. Also the realization of mobile robot teleoperation via ad-hoc networks, and recommendations of how to use existing adhoc routing protocol implementations in typical networked mobile robot scenarios are presented. Unfortunately, the default parameter settings of the available ad-hoc routing protocols lead to unsatisfying results and thus, modifications of the parameter settings are presented in order to achieve a suitable performance. Additionally, guidelines for the definition, setup, and evaluation of test scenarios for the application of wireless LAN ad-hoc networks for
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mobile robots are given. Also the assets and drawbacks of the several ad-hoc routing protocols with respect to the scenarios are discussed. Finally, some future prospects of applications in the area of mobile robot teleoperation and networked robots are given - e.g. the traffic shaping mechanism based on network feedback which can be used in wireless ad-hoc networks. It could be shown how existing communication technologies (e.g. WLAN) could be used to integrate heterogeneous teams of humans and mobile robots successfully. REFERENCES Birk, A. and Condea, C. (2006). Mobile robot communication without the drawbacks of wireless networking. In I. Noda, A. Jacoff, A. Bredenfeld, and Y. Takahashi (eds.), RoboCup 2005: Robot Soccer World Cup IX, volume 4020 of Lecture Notes in Artificial Intelligence (LNAI), 585 – 592. Springer. Broch, J., Maltz, D.A., Johnson, D.B., Hu, Y.C., and Jetcheva, J. (1998). A performance comparison of multihop wireless ad hoc network routing protocols. In Mobile Computing and Networking, 85–97. Eck, D., Stahl, M., and Schilling, K. (2007). The Small Outdoor Rover MERLIN and its Assistance System for Tele-Operations. In Proc. of Int. Conf. on Field and Service Robotics, Chamonix, France. Lee, S., Sukhatme, G.S., Kim, G.J., and Park, C.M. (2005). Haptic teleoperation of a mobile robot: A user study. Presence: Teleoperators & Virtual Environments, 14(3), 345–365. Musial, M., Brandenburg, U.W., and Hommel, G. (2001). Success of an Inexpensive System Design: The Flying Robot MARVIN. In 16th Int. Unmanned Air Vehicle System Conf. (UAVs). Perkins, C., Royer, E., Das, S., and Marina, M. (2001). Performance comparison of two on-demand routing protocols for ad hoc networks. IEEE Personal Communications, 8(1), 16–28. Pezeshkian, N., Nguyen, H.G., and Burmeister, A. (2007). Unmanned ground vehicle radio relay deployment system for non-line-of-sight operations. In Proc. of the 13th IASTED Int. Conf. on Robotics and Applications, August 29-31, W¨ urzburg, Germany, RA2007. Zeiger, F., Kraemer, N., and Schilling, K. (2008a). Parameter tuning of routing protocols to improve the performance of mobile robot teleoperation via wireless ad-hoc networks. In 5th International Conference on Informatics, Automation and Robotics (ICINCO 2008). Zeiger, F., Kr¨amer, N., and Schilling, K. (2008b). Commanding mobile robots via wireless ad-hoc networks - a comparison of four ad-hoc routing protocol implementations. In IEEE Int. Conf. on Robotics and Automation (ICRA 2008). Zeiger, F., Krmer, N., Sauer, M., and Schilling, K. (2008c). Challenges in Realizing Ad-Hoc Networks based on Wireless LAN with Mobile Robots. In Workshop on Wireless Multihop Communications in Networked Robotics (WMCNR 2008). Zeiger, F., Sauer, M., and Schilling;, K. (2008d). Video Transmission with Adaptive Quality based on Network Feedback for Mobile Robot Teleoperation in Wireless Multi-Hop Networks. In 5th Int. Conf. on Informatics, Automation and Robotics (ICINCO 2008).