- Email: [email protected]
CBRNE reconnaissance with an unmanned vehicle - A semi-autonomous approach -
2nd IFAC Symposium on Telematics Applications Politehnica University, Timisoara, Romania October 5-8, 2010
CBRNE reconnaissance with an unmanned vehicle - A semi-autonomous approach Frank E. Schneider, Timo Röhling, Bernd Brüggemann, and Dennis Wildermuth Fraunhofer Institute for Communication, Information Processing and Ergonomics (FKIE) Neuenahrerstrasse 20, 53343 Wachtberg, Germany (e-mail: [email protected]) Abstract: This paper presents a research project for a CBRNE hazard detection robot prototype for the German Military Forces. One of the main design principles is the usage of commercially available sensors that can be exchanged and upgraded easily without touching the underlying robot platform. First assistance functions on the way to semi-autonomy, like GPS waypoint following are introduced. Keywords: CBRNE, hazard detection, teleoperation In this paper, we describe the development of our CBRNE robot for the German Military Forces and the preliminary evaluation in a (simulated) CRN hazard scenario. One important design goal for the system is the fast and easy introduction into service. Therefore, we rely on sensor equipment, which is already in use in the German forces or at least commercial off-the-shelf. In principle, all deployed sensors can be used independently from the robot base, turning the vehicle into a mobile toolbox.
1. INTRODUCTION One of the principal motivations for the deployment of robot systems in the military domain is the desire to minimise the exposure of soldiers. Tasks such as explosive ordnance disposal or the identification of chemical, biological, radiological, and nuclear hazards pose great threat to human personnel. The reconnaissance of nuclear, chemical, or explosive devices becomes increasingly important in our days. On one hand, threats by terrorist groups can cause great damage with relatively small effort. On the other hand, disasters in industrial areas may release dangerous and not easily detectable chemicals. If such an emergency occurs, information about what has happened and how the situation develops is crucial for an effective response. However, it is difficult to explore these scenarios without mortal danger for the involved action force, be it fire fighters, army, or police. Unmanned systems help reduce the number of human beings which are required within the danger zone. The robot can be sent ahead, assess the situation at hand and return information and sensor data back to the controller.
Several other efforts in the development of CBRNE systems show the importance of this topic. The Canadian Forces employ a tele-operated all-terrain vehicle with a mounted integrated CBRN sensor suite (Penzes, 2006). This is used in combination with a ground station that belongs to a remote mobile command post. As one major result, the importance of proper training for the prospective users is mentioned. Similar to our system, this problem is partially mitigated by employing sensors that are already in use and the corresponding well-known analysis software. (Neilsen et al., 2006) emphasise that robots are important to keep humans away from hazardous environments. They improve upon a purely tele-operated system by introducing semiautonomous features, which can help to reduce the amount of training that the operator needs. (Jasiobedzki et al., 2009) describe a system to increase the situation awareness of the operator, which is called Crime Scene Modeller. Its primary purpose is the construction of a three-dimensional model that contains points of interests (e.g. chemical, biological, radiological, and nuclear agents).
While a robot that operates completely autonomously would free up valuable human resources for other important tasks, a partially autonomous or even a fully remote-controlled vehicle already provides enough security benefits to justify immediate deployment. Basic requirements, which are to be met, include the ability to
operate in areas with high radioactive dose output, perform long-term measurements in a contaminated area, gather samples, monitor spatial intensity variations of contamination, and communicate findings in real time over an encrypted data link.
978-3-902661-84-5/10/$20.00 © 2010 IFAC
There has been a considerable amount of research related to the automated source localization of chemical agents. Most applied methods emulate the biological olfactory systems of lobsters, ants, and moths (Zarzhitsky et al., 2004). The chemotaxis approach consists of following the local concentration gradient, which works best if the chemical agent is spread mostly by diffusion. The anemotaxis approach consists of following the upwind direction, which works best if the chemical agent is spread mostly by convection without turbulences. A second class of techniques estimates the 122
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TA 2010 Timisoara, Romania, Oct 5-8, 2010
Although the operator should be in control of the robot at all times, it is not necessary for the robot to be fully remote controlled. In fact, assistance functions that provide a certain degree of autonomy for routine tasks enable the operator to focus on high-level mission control. This will reduce fatigue and improve the response time in critical situations.
spread by numerical simulation of the assumed environmental conditions, see e.g. (Kathirgamanthan et al., 2002) or (Christopoulos and Roumeliotis, 2005a, b). The principal drawback of all these approaches so far is that their assumptions about the environment are easily violated in actual deployments. Therefore, our short-term autonomy plans focus on assistance functions for navigation and other simple routine tasks. A GPS-based navigation is the first step away from pure remote control. Nevertheless, the automated discovery of pollution sources remains a long-term goal of the system.
3. THE ROBOT PLATFORM The basic platform for our CBRNE robot is the wheeled version of the QinetiQ Longcross with an additional Diesel power generator (see Fig. 1). The robot itself weighs about 340 kg and has a payload capacity of at least 150 kg according to the manufacturer. The compartment consists of carbon-fibre and is environmentally shielded.
The remainder of this paper is structured as follows: We outline the requirements for a CBRNE robot in section II. Then we describe the robot platform in more detail in section III. Section IV shortly presents the GPS-based semiautonomous navigation approach. The different types of sensors are covered in section V. The user interface and the connection between robot and its control station is described in section VI, and a test run of the system in its current state is detailed in section VII.
While the compartment is in fact sturdy enough to withstand small arms weapon fire, this is of no tactical significance, because most military weapons have much higher piercing force.
2. REQUIREMENTS The given scenario leads to several constraints, which have to be observed for the development of the CBRNE robot. According to military experts, the robot itself must fulfil the following specifications:
Fast implementation of a robust, dependable, and flexible mobile system Choice of wheels or tracks for propelling Diesel-electric drive, about 25 km/h Payload of at least 150 kg Gasproof and waterproof
Several reasons have led to the additional requirement that commercial (COTS) and in-use CRNE sensor components should be used. Firstly, these systems are usually easier to purchase and less expensive than prototypes or custom solutions. Secondly, it is not necessary to develop new training methods for equipment that is already in use by the force.
Fig. 1. The experimental CBRNE platform. The metal boxes contain various CBRNE sensors, which may trigger an alarm both locally and at the control station. The vehicle can reach a top speed of 4 m/s and has battery capacity for about 30 minutes; the diesel generator extends the runtime to approximately 90 minutes. The operational range is around 3000 m. The wheels on each side are rigidly connected to the gear mechanism, resulting in a behaviour that is very similar to a track drive, albeit with less traction. The robot can cope with very difficult terrain and is able to turn around on the spot. However, as can be expected, the latter draws a substantial amount of motor current, significantly reducing the operation time. The wheels can be exchanged to tracks, which give the vehicle substantially more off-road capabilities.
However, the availability of such sensors gives an additional constraint. As of today, there are no biological sensors available which can perform the necessary task of identifying biological warfare agents while still being transportable on a mobile platform. Current best practice is to collect samples and take them to a suitably equipped laboratory. Thus, the detection focus for CBRNE robots lies on chemical, radiological, and nuclear agents. Communication is another crucial issue. During the mission, the robot will have to send and receive a significant amount of data. Therefore, several different communication channels have to be available:
In order to provide sufficient situation awareness, the robot is equipped with a number of non-CBRNE-related sensors. The TopCon Legacy-E+ GPS receiver is able to receive both L1/L2 GPS and GLONASS satellite data with an RTK (OTF) accuracy below 25 mm according to the manufacturer. This is the main sensor for the GPS waypoint navigation. A rotatable camera provides visual feedback for the operator and is therefore the main sensor for remote controlled operation.
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In this configuration space, a variant of expansive-spaces trees (EST) is used for the search of appropriate motion controls. The EST algorithms belong to the probabilistic roadmap techniques for path planning. For a given target state, a roadmap is generated by growing a random tree Τ = (V, E) consisting of nodes V and transitions E which represent possible paths for the robot. A node v V consists of a state in the configuration space and additionally some bookkeeping information like the time required to reach the node.
Future work will include the installation of a mechanical arm to gather samples. The arm will be outfitted with an extra camera to allow more precise gripping. 4. NAVIGATION As already mentioned in the introduction our aim was not fully autonomous navigation, since that is hard to achieve or even sometimes not desirable in the field of CBRNE reconnaissance. Instead, we provided GPS-based semiautonomous navigation as a first means of assistance for the operators. There are two important services used for navigation, named local and global navigation. They handle the autonomous navigation towards a given GPS coordinate, including collision avoidance.
Our EST algorithm performs a randomised search for good sequences of velocity commands, which steer the robot towards the target. This is achieved by successively 1) selecting a node v with state q, 2) generating a new node v´ with state r by choosing a pair of velocities (vr; wr) reachable from q within one time interval and computing the new state r, and 3) finally adding the node v´ to V and the new transition (v → v´) to E, if both are admissible, i.e. if the trajectory from q to r is collision-free.
The global navigation service has the task to steer the robot in a way that it reaches every point on a GPS waypoint list in the given order. The service receives a list of GPS waypoints and then transfers the first GPS data into a local robot coordinate system that is relative to the robot with the robot placed at the origin. These local coordinates are then send to the local navigation which tries to steer the robot on a collision free path that reaches the target. The global navigation service will ensure that the robot eventually reaches the GPS coordinates. That means it checks if the robot gets closer to the GPS coordinates and, if not, will resend the target. If the coordinates are reached and there is still a next GPS waypoint on the list, the local coordinates of this next GPS waypoint are calculated and again send to the local navigation.
In order to achieve an efficient target-directed expansion of the tree, the node selection is governed by an importance function, which takes the distance to the target state into account. Fig. 2 shows an example EST built by our implementation of the technique.
Fig. 2. An example for an expansive-spaces tree generated by the local navigation. Obstacles are shown in black; R denotes the robot and T the target point. The tree is shown in blue and the selected path is highlighted in green.
Fig. 3. The modular sensor platform. 5. SENSORS
The local navigation service has the task to avoid collisions while driving towards a goal given in the before mentioned local robot coordinate system. We utilise the approach described in (Hoeller & Schulz, 2007) and provide only a brief overview here. Obstacles are detected by the local navigation services by using the laser scanners and are marked within a local map. The approach then tries to find a collision free path within this map data structure by carrying out a search in configuration space. A configuration xk = (x, y, θ, v, w)kT at time k consists of the robot position (x, y)T and heading θ. In addition, the current translational velocity v and the rotational velocity w are also part of the configuration.
Depending on the mission parameters, different sets of sensors will be required. Therefore, the sensor platform of the CBRNE robot is constructed in a modular fashion, so that it is possible to switch between different sensors. Fig. 3 depicts the typical configuration for our robot. The large box on the left is the MDS sensor, which is designed to detect arbitrary radiation sources. Near the top is the identiFinder, another sensor to identify radiological threats. At the bottom, there is the combination of two different chemical sensors, the MultiRAE+ and the LCD3.3.
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Because of the modular setup, any sensor can be removed at any time to be used in a stand-alone mode. This allows sensors to be used manually, should the need arise.
ionise the gas. Depending on the substance, different amounts of the UV light are absorbed, leading to different levels of ionisation, which can be measured by the sensor. Special for the MultiRAE+ is that it has up to five different sensors. An infrared light sensor detects CO2. In addition, the oxygen level is measured all the time. The described PID sensor is suitable for a broad range of organic vapours. By changing the electrochemical toxic sensor, several different inorganic toxic gases can be detected. Again the disadvantage is, that one must have an idea of which toxic agent may be found in the target area.
5.1 Lightweight Chemical Detector The Lightweight Chemical Detector (LCD) is a chemical sensor. It samples the air continuously, searching for different chemical warfare agents (CWAs) and toxic industrial chemicals (TICs). The alarm is triggered if either a certain concentration threshold is exceeded, or the accumulated dose over time becomes hazardous for human beings. For an example output of the LCD, see Fig. 4.
5.3 MDS
The LCD uses a kind of Ion Mobility Spectrometry, see e.g. (St. Louis et al., 1990). The sensors continuously take in ambient air, which is directed into the ionisation chamber. This chamber produces ions from the air as well as possible sample ions of chemicals in that air. A cluster of those ions is passed on to a drift area with two different drift regions, one working with negative ions and another working with positive ones. By detecting the speed and amount of ions, the different substances can be analysed and distinguished. After a substance has been detected, the LCD needs about 120 seconds to recover.
The Mobile Detection System (MDS) is a gamma ray sensor. Its purpose is to be used in helicopters or non-armoured vehicles, i.e. fast moving vehicles. It can incorporate GPS information to mark its measurements on a map. This facilitates detailed analysis after the mission is completed, but also during the mission. An example output can be seen in Fig. 5. The gamma radiation is measured by a large-volume synthetic scintillator. It uses the NBR (natural background rejection) to find even small amounts of radiation. With the help of the NBR technique, the MDS is able to distinguish between natural (background) radiation and artificial radiation. Even an artificial radiation level below the natural radiation background level can be detected. As the natural radiation is fluctuating depending on the location, the MDS is designed to find artificial sources of radiation in a large area.
Fig. 4. Output of the LCD sensor from the CBRNE robot. This analysis is possible due to a data set, which is predefined in the software of the LCD. Whereas it is possible to store data from several different chemicals, it is recommended not to have more than ten different chemicals stored. For this reason, it is necessary to determine in advance, which chemical agents might be encountered in the target area. We mitigate this disadvantage by employing two devices simultaneously, one for TICs and a second for CWAs.
Fig. 5. Graphical output of the MDS sensory system with plotted way. The synthetic scintillator is supersensitive and has a limit for detecting up to 20 µSv/h. It also has a built-in Geiger detector to be useful with radiation sources, which are stronger than that, up to 1 Sv/h. Therefore, it can also be used in more classical missions like measuring the fallout after a radiation disaster. With an additional sensor, the MDS is also capable of finding neutron sources.
5.2 MultiRAE+ The MultiRAE+ is a multi-gas sensor designed to provide monitoring of CO2, toxic gases, oxygen and combustible gases. It uses different sensors to identify gases in the air, among them a photo ionisation detector. In this detector, the gas is illuminated with an UV lamp. The high-energy photons
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5.4 ICX identiFinder
accordingly. We decided to use Perle IOLAN SDS serialover-LAN converters as a means to forward serial ports over a wireless link or fibre wire. The sensors are connected to one I/O converter on the robot itself. The converter forwards the data stream to a corresponding box connected to the control station computer, so that the operator can handle the sensors as if they were directly connected to the workstation.
The identiFinder is a sensor to detect gamma radiation. In contrast to the MDS, the identiFinder is not able to distinguish between natural and artificial radiation. Instead, it can identify the type of radioactive nuclide. For this task, the identiFinder uses a NaJ(Ti) (sodium iodide/thallium) detector as gamma spectrum analyser. It has a measurement range up to 500 µSv/h. Above this limit, the identiFinder uses a Geiger-Müller tube. With the help of a database, the identiFinder is able to identify the nuclide. When detecting a gamma source, the identiFinder records a spectrum and compares it to all known spectrums. Therefore, the identification of the gamma source is only as good as the data in the nuclide database.
The advantage of this setup is the ability to employ the standard analysis tools that are shipped with the various sensors. No additional training for the operator beyond the knowledge to control the sensors themselves is needed. Introduction of a new type of sensor requires little more work than connecting the device to the I/O forwarder and installing the corresponding evaluation software on the control station. The only precondition is that each sensor must be equipped with a compatible PC connector.
6. USER INTERFACE
Although there is no technical limitation regarding the actual setup of the control station, we found it convenient to install all required equipment into the trunk compartment of a Ford Transit transporter. The storage space is large enough to accommodate a control station that can be manned by two operators, as well as the necessary radio transmitters, and the robot itself (see Fig. 7).
The robots GUI consists of a multifunctional graphical Qt based user interface (see Fig. 6). The main two functionalities of interest in this context are the teleoperation interface and the GPS waypoint navigation. The teleoperation interface provides a live camera picture. All camera parameters (zoom, focus, day/night etc.) can be controlled through the GUI. By default, we use a joystick for steering the robot, but all devices that are supported through LINUX Human Interface Device (HID) service can be used. The GPS waypoint navigation makes intensive use of georeferenced maps and aerial photos. The computer mouse is used to set, modify, and delete waypoints into the map/photo. In addition, a search area, which has to be covered, can be specified by a polygon. The navigation service will the autonomously meander the UGV through the area.
Fig. 7. Control station in a van consisting of a robot operator station (left) and a CBRNE analysis station (right). In order to achieve peak performance and efficiency, two operators share the workload of running the CBRNE system. One operator is responsible for the navigation of the robot platform, while the other operator concentrates on the analysis and evaluation of the incoming sensor data. The current setup still requires a great deal of manual control to navigate the robot. 7. DEMONSTRATION
Fig. 6. Example GUI configuration; camera picture (upper middle); aerial photo with waypoints (lower middle).
With the CBRNE robot several test runs in different environments and with different samples were performed. We give one particular run as example of the general setting (see Fig. 8).
Since one of the design goals is to keep the sensors independent from the underlying robot platform, the connection to the control station has to be established 126
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Locations 1 and 2 mark the starting positions of a reconnaissance robot and CBRNE robot respectively. Location A contains a radiological sample, location B is contaminated with a testing fluid that emulates a dangerous gaseous chemical agent. The mobile control station is positioned at location 3.
warfare agents, and it is designed to be operated through a mobile control station. All sensor readings and robot status information are transparently forwarded to the operators and displayed in real time. The soundness of the design has been tested in a controlled environment. Important future work will include the installation of a mechanical arm, which is required to gather samples for later analysis, and more extensive assistance functions for routine tasks and 3D mapping of the surveyed environment. REFERENCES Christopoulos, V. and S. Roumeliotis (2005a). Multi robot trajectory generation for single source explosion parameter estimation. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2803–2809. Christopoulos, V. and S. Roumeliotis (2005b). Adaptive sensing for instantaneous gas release parameter estimation. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4450–4456. Hoeller, F. and D. Schulz (2007). Accompanying persons with a mobile robot using motion prediction and probabilistic roadmaps. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1260–1265. Jasiobedzki, P., H.-K. Ng, M. Bondy and C.H. McDiarmid (2009). C2SM: a mobile system for detecting and 3D mapping of chemical, radiological, and nuclear contamination. In: Proceedings of Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII. Kathirgamanthan, P., R. McKibbin and R. McLachlan (2002). Source term estimation of pollution from an instantaneous point source. Research Letters in the Information and Mathematical Sciences, 3, pp. 59–67. Neilsen, C.W., D.I. Gertman, D.J. Bruemmer, R.S. Hartley and M.C. Walton (2008). Evaluating robot technologies as tools to explore radiological and other hazardous environments. In: Proceedings of American Nuclear Society Emergency Planning and Response, and Robotics and Security Systems Joint Topical Meeting, Albuquerque, NM, USA. Penzes, S.G. (2006). Multiagent tactical sentry (MATS) project review. In: Proceedings of the International Society for Optical Engineering (SPIE), Kissimmee, FL, USA. St. Louis, R.H., H.H. Hill Jr. and G.A. Eiceman (1990). Ion Mobility Spectrometry in Analytical Chemistry. Critical Reviews in Analytical Chemistry, 21, pp. 321–355. Zarzhitsky, D., D. Spears, W. Spears and D. Thayer (2004). A fluid dynamics approach to multi-robot chemical plume tracing. In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 3, pp. 1476–1477.
Fig. 8. Schematic overview of the demonstration test run. At first, a reconnaissance unit explores the area, discovering potential NBC threats. Thus, the recon unit is backtracked and the CBRNE robot is deployed. At location A, the robot’s MDS triggers an alert for an artificial gamma source at a range of about 50cm, followed by a more detailed analysis of the identiFinder. After approximately 100s, the radioactive material can be correctly identified. At location B, the LCD sensor almost instantly detects the deployed aerosol, which emulates a dangerous chemical warfare agent (see Fig. 9). The system was also tested with the German NBC Defense School in Sonthofen. The tests showed that most of the requirements were meet and that the hardware reached already quite mature level. Because of these tests, the system will be used as a prototype for a starting procurement.
Fig. 9. The robot encounters the suspicious gas emission at location B. 8. CONCLUSION In this paper, we presented an iteratively evolutionary development of a CBRNE robot system. Within very little time (about 10 months), this robot was built on a COTS wheel-drive platform with in-service sensor systems. It is able to identify different threats like nuclear or chemical 127
CBRNE reconnaissance with an unmanned vehicle - A semi-autonomous approach Frank E. Schneider, Timo Röhling, Bernd Brüggemann, and Dennis Wildermuth Fraunhofer Institute for Communication, Information Processing and Ergonomics (FKIE) Neuenahrerstrasse 20, 53343 Wachtberg, Germany (e-mail: [email protected]) Abstract: This paper presents a research project for a CBRNE hazard detection robot prototype for the German Military Forces. One of the main design principles is the usage of commercially available sensors that can be exchanged and upgraded easily without touching the underlying robot platform. First assistance functions on the way to semi-autonomy, like GPS waypoint following are introduced. Keywords: CBRNE, hazard detection, teleoperation In this paper, we describe the development of our CBRNE robot for the German Military Forces and the preliminary evaluation in a (simulated) CRN hazard scenario. One important design goal for the system is the fast and easy introduction into service. Therefore, we rely on sensor equipment, which is already in use in the German forces or at least commercial off-the-shelf. In principle, all deployed sensors can be used independently from the robot base, turning the vehicle into a mobile toolbox.
1. INTRODUCTION One of the principal motivations for the deployment of robot systems in the military domain is the desire to minimise the exposure of soldiers. Tasks such as explosive ordnance disposal or the identification of chemical, biological, radiological, and nuclear hazards pose great threat to human personnel. The reconnaissance of nuclear, chemical, or explosive devices becomes increasingly important in our days. On one hand, threats by terrorist groups can cause great damage with relatively small effort. On the other hand, disasters in industrial areas may release dangerous and not easily detectable chemicals. If such an emergency occurs, information about what has happened and how the situation develops is crucial for an effective response. However, it is difficult to explore these scenarios without mortal danger for the involved action force, be it fire fighters, army, or police. Unmanned systems help reduce the number of human beings which are required within the danger zone. The robot can be sent ahead, assess the situation at hand and return information and sensor data back to the controller.
Several other efforts in the development of CBRNE systems show the importance of this topic. The Canadian Forces employ a tele-operated all-terrain vehicle with a mounted integrated CBRN sensor suite (Penzes, 2006). This is used in combination with a ground station that belongs to a remote mobile command post. As one major result, the importance of proper training for the prospective users is mentioned. Similar to our system, this problem is partially mitigated by employing sensors that are already in use and the corresponding well-known analysis software. (Neilsen et al., 2006) emphasise that robots are important to keep humans away from hazardous environments. They improve upon a purely tele-operated system by introducing semiautonomous features, which can help to reduce the amount of training that the operator needs. (Jasiobedzki et al., 2009) describe a system to increase the situation awareness of the operator, which is called Crime Scene Modeller. Its primary purpose is the construction of a three-dimensional model that contains points of interests (e.g. chemical, biological, radiological, and nuclear agents).
While a robot that operates completely autonomously would free up valuable human resources for other important tasks, a partially autonomous or even a fully remote-controlled vehicle already provides enough security benefits to justify immediate deployment. Basic requirements, which are to be met, include the ability to
operate in areas with high radioactive dose output, perform long-term measurements in a contaminated area, gather samples, monitor spatial intensity variations of contamination, and communicate findings in real time over an encrypted data link.
978-3-902661-84-5/10/$20.00 © 2010 IFAC
There has been a considerable amount of research related to the automated source localization of chemical agents. Most applied methods emulate the biological olfactory systems of lobsters, ants, and moths (Zarzhitsky et al., 2004). The chemotaxis approach consists of following the local concentration gradient, which works best if the chemical agent is spread mostly by diffusion. The anemotaxis approach consists of following the upwind direction, which works best if the chemical agent is spread mostly by convection without turbulences. A second class of techniques estimates the 122
10.3182/20101005-4-RO-2018.00040
TA 2010 Timisoara, Romania, Oct 5-8, 2010
Although the operator should be in control of the robot at all times, it is not necessary for the robot to be fully remote controlled. In fact, assistance functions that provide a certain degree of autonomy for routine tasks enable the operator to focus on high-level mission control. This will reduce fatigue and improve the response time in critical situations.
spread by numerical simulation of the assumed environmental conditions, see e.g. (Kathirgamanthan et al., 2002) or (Christopoulos and Roumeliotis, 2005a, b). The principal drawback of all these approaches so far is that their assumptions about the environment are easily violated in actual deployments. Therefore, our short-term autonomy plans focus on assistance functions for navigation and other simple routine tasks. A GPS-based navigation is the first step away from pure remote control. Nevertheless, the automated discovery of pollution sources remains a long-term goal of the system.
3. THE ROBOT PLATFORM The basic platform for our CBRNE robot is the wheeled version of the QinetiQ Longcross with an additional Diesel power generator (see Fig. 1). The robot itself weighs about 340 kg and has a payload capacity of at least 150 kg according to the manufacturer. The compartment consists of carbon-fibre and is environmentally shielded.
The remainder of this paper is structured as follows: We outline the requirements for a CBRNE robot in section II. Then we describe the robot platform in more detail in section III. Section IV shortly presents the GPS-based semiautonomous navigation approach. The different types of sensors are covered in section V. The user interface and the connection between robot and its control station is described in section VI, and a test run of the system in its current state is detailed in section VII.
While the compartment is in fact sturdy enough to withstand small arms weapon fire, this is of no tactical significance, because most military weapons have much higher piercing force.
2. REQUIREMENTS The given scenario leads to several constraints, which have to be observed for the development of the CBRNE robot. According to military experts, the robot itself must fulfil the following specifications:
Fast implementation of a robust, dependable, and flexible mobile system Choice of wheels or tracks for propelling Diesel-electric drive, about 25 km/h Payload of at least 150 kg Gasproof and waterproof
Several reasons have led to the additional requirement that commercial (COTS) and in-use CRNE sensor components should be used. Firstly, these systems are usually easier to purchase and less expensive than prototypes or custom solutions. Secondly, it is not necessary to develop new training methods for equipment that is already in use by the force.
Fig. 1. The experimental CBRNE platform. The metal boxes contain various CBRNE sensors, which may trigger an alarm both locally and at the control station. The vehicle can reach a top speed of 4 m/s and has battery capacity for about 30 minutes; the diesel generator extends the runtime to approximately 90 minutes. The operational range is around 3000 m. The wheels on each side are rigidly connected to the gear mechanism, resulting in a behaviour that is very similar to a track drive, albeit with less traction. The robot can cope with very difficult terrain and is able to turn around on the spot. However, as can be expected, the latter draws a substantial amount of motor current, significantly reducing the operation time. The wheels can be exchanged to tracks, which give the vehicle substantially more off-road capabilities.
However, the availability of such sensors gives an additional constraint. As of today, there are no biological sensors available which can perform the necessary task of identifying biological warfare agents while still being transportable on a mobile platform. Current best practice is to collect samples and take them to a suitably equipped laboratory. Thus, the detection focus for CBRNE robots lies on chemical, radiological, and nuclear agents. Communication is another crucial issue. During the mission, the robot will have to send and receive a significant amount of data. Therefore, several different communication channels have to be available:
In order to provide sufficient situation awareness, the robot is equipped with a number of non-CBRNE-related sensors. The TopCon Legacy-E+ GPS receiver is able to receive both L1/L2 GPS and GLONASS satellite data with an RTK (OTF) accuracy below 25 mm according to the manufacturer. This is the main sensor for the GPS waypoint navigation. A rotatable camera provides visual feedback for the operator and is therefore the main sensor for remote controlled operation.
Broadband communication for data and video Wireless and fibre optics connection Digital (COFDM) Ethernet 123
TA 2010 Timisoara, Romania, Oct 5-8, 2010
In this configuration space, a variant of expansive-spaces trees (EST) is used for the search of appropriate motion controls. The EST algorithms belong to the probabilistic roadmap techniques for path planning. For a given target state, a roadmap is generated by growing a random tree Τ = (V, E) consisting of nodes V and transitions E which represent possible paths for the robot. A node v V consists of a state in the configuration space and additionally some bookkeeping information like the time required to reach the node.
Future work will include the installation of a mechanical arm to gather samples. The arm will be outfitted with an extra camera to allow more precise gripping. 4. NAVIGATION As already mentioned in the introduction our aim was not fully autonomous navigation, since that is hard to achieve or even sometimes not desirable in the field of CBRNE reconnaissance. Instead, we provided GPS-based semiautonomous navigation as a first means of assistance for the operators. There are two important services used for navigation, named local and global navigation. They handle the autonomous navigation towards a given GPS coordinate, including collision avoidance.
Our EST algorithm performs a randomised search for good sequences of velocity commands, which steer the robot towards the target. This is achieved by successively 1) selecting a node v with state q, 2) generating a new node v´ with state r by choosing a pair of velocities (vr; wr) reachable from q within one time interval and computing the new state r, and 3) finally adding the node v´ to V and the new transition (v → v´) to E, if both are admissible, i.e. if the trajectory from q to r is collision-free.
The global navigation service has the task to steer the robot in a way that it reaches every point on a GPS waypoint list in the given order. The service receives a list of GPS waypoints and then transfers the first GPS data into a local robot coordinate system that is relative to the robot with the robot placed at the origin. These local coordinates are then send to the local navigation which tries to steer the robot on a collision free path that reaches the target. The global navigation service will ensure that the robot eventually reaches the GPS coordinates. That means it checks if the robot gets closer to the GPS coordinates and, if not, will resend the target. If the coordinates are reached and there is still a next GPS waypoint on the list, the local coordinates of this next GPS waypoint are calculated and again send to the local navigation.
In order to achieve an efficient target-directed expansion of the tree, the node selection is governed by an importance function, which takes the distance to the target state into account. Fig. 2 shows an example EST built by our implementation of the technique.
Fig. 2. An example for an expansive-spaces tree generated by the local navigation. Obstacles are shown in black; R denotes the robot and T the target point. The tree is shown in blue and the selected path is highlighted in green.
Fig. 3. The modular sensor platform. 5. SENSORS
The local navigation service has the task to avoid collisions while driving towards a goal given in the before mentioned local robot coordinate system. We utilise the approach described in (Hoeller & Schulz, 2007) and provide only a brief overview here. Obstacles are detected by the local navigation services by using the laser scanners and are marked within a local map. The approach then tries to find a collision free path within this map data structure by carrying out a search in configuration space. A configuration xk = (x, y, θ, v, w)kT at time k consists of the robot position (x, y)T and heading θ. In addition, the current translational velocity v and the rotational velocity w are also part of the configuration.
Depending on the mission parameters, different sets of sensors will be required. Therefore, the sensor platform of the CBRNE robot is constructed in a modular fashion, so that it is possible to switch between different sensors. Fig. 3 depicts the typical configuration for our robot. The large box on the left is the MDS sensor, which is designed to detect arbitrary radiation sources. Near the top is the identiFinder, another sensor to identify radiological threats. At the bottom, there is the combination of two different chemical sensors, the MultiRAE+ and the LCD3.3.
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Because of the modular setup, any sensor can be removed at any time to be used in a stand-alone mode. This allows sensors to be used manually, should the need arise.
ionise the gas. Depending on the substance, different amounts of the UV light are absorbed, leading to different levels of ionisation, which can be measured by the sensor. Special for the MultiRAE+ is that it has up to five different sensors. An infrared light sensor detects CO2. In addition, the oxygen level is measured all the time. The described PID sensor is suitable for a broad range of organic vapours. By changing the electrochemical toxic sensor, several different inorganic toxic gases can be detected. Again the disadvantage is, that one must have an idea of which toxic agent may be found in the target area.
5.1 Lightweight Chemical Detector The Lightweight Chemical Detector (LCD) is a chemical sensor. It samples the air continuously, searching for different chemical warfare agents (CWAs) and toxic industrial chemicals (TICs). The alarm is triggered if either a certain concentration threshold is exceeded, or the accumulated dose over time becomes hazardous for human beings. For an example output of the LCD, see Fig. 4.
5.3 MDS
The LCD uses a kind of Ion Mobility Spectrometry, see e.g. (St. Louis et al., 1990). The sensors continuously take in ambient air, which is directed into the ionisation chamber. This chamber produces ions from the air as well as possible sample ions of chemicals in that air. A cluster of those ions is passed on to a drift area with two different drift regions, one working with negative ions and another working with positive ones. By detecting the speed and amount of ions, the different substances can be analysed and distinguished. After a substance has been detected, the LCD needs about 120 seconds to recover.
The Mobile Detection System (MDS) is a gamma ray sensor. Its purpose is to be used in helicopters or non-armoured vehicles, i.e. fast moving vehicles. It can incorporate GPS information to mark its measurements on a map. This facilitates detailed analysis after the mission is completed, but also during the mission. An example output can be seen in Fig. 5. The gamma radiation is measured by a large-volume synthetic scintillator. It uses the NBR (natural background rejection) to find even small amounts of radiation. With the help of the NBR technique, the MDS is able to distinguish between natural (background) radiation and artificial radiation. Even an artificial radiation level below the natural radiation background level can be detected. As the natural radiation is fluctuating depending on the location, the MDS is designed to find artificial sources of radiation in a large area.
Fig. 4. Output of the LCD sensor from the CBRNE robot. This analysis is possible due to a data set, which is predefined in the software of the LCD. Whereas it is possible to store data from several different chemicals, it is recommended not to have more than ten different chemicals stored. For this reason, it is necessary to determine in advance, which chemical agents might be encountered in the target area. We mitigate this disadvantage by employing two devices simultaneously, one for TICs and a second for CWAs.
Fig. 5. Graphical output of the MDS sensory system with plotted way. The synthetic scintillator is supersensitive and has a limit for detecting up to 20 µSv/h. It also has a built-in Geiger detector to be useful with radiation sources, which are stronger than that, up to 1 Sv/h. Therefore, it can also be used in more classical missions like measuring the fallout after a radiation disaster. With an additional sensor, the MDS is also capable of finding neutron sources.
5.2 MultiRAE+ The MultiRAE+ is a multi-gas sensor designed to provide monitoring of CO2, toxic gases, oxygen and combustible gases. It uses different sensors to identify gases in the air, among them a photo ionisation detector. In this detector, the gas is illuminated with an UV lamp. The high-energy photons
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5.4 ICX identiFinder
accordingly. We decided to use Perle IOLAN SDS serialover-LAN converters as a means to forward serial ports over a wireless link or fibre wire. The sensors are connected to one I/O converter on the robot itself. The converter forwards the data stream to a corresponding box connected to the control station computer, so that the operator can handle the sensors as if they were directly connected to the workstation.
The identiFinder is a sensor to detect gamma radiation. In contrast to the MDS, the identiFinder is not able to distinguish between natural and artificial radiation. Instead, it can identify the type of radioactive nuclide. For this task, the identiFinder uses a NaJ(Ti) (sodium iodide/thallium) detector as gamma spectrum analyser. It has a measurement range up to 500 µSv/h. Above this limit, the identiFinder uses a Geiger-Müller tube. With the help of a database, the identiFinder is able to identify the nuclide. When detecting a gamma source, the identiFinder records a spectrum and compares it to all known spectrums. Therefore, the identification of the gamma source is only as good as the data in the nuclide database.
The advantage of this setup is the ability to employ the standard analysis tools that are shipped with the various sensors. No additional training for the operator beyond the knowledge to control the sensors themselves is needed. Introduction of a new type of sensor requires little more work than connecting the device to the I/O forwarder and installing the corresponding evaluation software on the control station. The only precondition is that each sensor must be equipped with a compatible PC connector.
6. USER INTERFACE
Although there is no technical limitation regarding the actual setup of the control station, we found it convenient to install all required equipment into the trunk compartment of a Ford Transit transporter. The storage space is large enough to accommodate a control station that can be manned by two operators, as well as the necessary radio transmitters, and the robot itself (see Fig. 7).
The robots GUI consists of a multifunctional graphical Qt based user interface (see Fig. 6). The main two functionalities of interest in this context are the teleoperation interface and the GPS waypoint navigation. The teleoperation interface provides a live camera picture. All camera parameters (zoom, focus, day/night etc.) can be controlled through the GUI. By default, we use a joystick for steering the robot, but all devices that are supported through LINUX Human Interface Device (HID) service can be used. The GPS waypoint navigation makes intensive use of georeferenced maps and aerial photos. The computer mouse is used to set, modify, and delete waypoints into the map/photo. In addition, a search area, which has to be covered, can be specified by a polygon. The navigation service will the autonomously meander the UGV through the area.
Fig. 7. Control station in a van consisting of a robot operator station (left) and a CBRNE analysis station (right). In order to achieve peak performance and efficiency, two operators share the workload of running the CBRNE system. One operator is responsible for the navigation of the robot platform, while the other operator concentrates on the analysis and evaluation of the incoming sensor data. The current setup still requires a great deal of manual control to navigate the robot. 7. DEMONSTRATION
Fig. 6. Example GUI configuration; camera picture (upper middle); aerial photo with waypoints (lower middle).
With the CBRNE robot several test runs in different environments and with different samples were performed. We give one particular run as example of the general setting (see Fig. 8).
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Locations 1 and 2 mark the starting positions of a reconnaissance robot and CBRNE robot respectively. Location A contains a radiological sample, location B is contaminated with a testing fluid that emulates a dangerous gaseous chemical agent. The mobile control station is positioned at location 3.
warfare agents, and it is designed to be operated through a mobile control station. All sensor readings and robot status information are transparently forwarded to the operators and displayed in real time. The soundness of the design has been tested in a controlled environment. Important future work will include the installation of a mechanical arm, which is required to gather samples for later analysis, and more extensive assistance functions for routine tasks and 3D mapping of the surveyed environment. REFERENCES Christopoulos, V. and S. Roumeliotis (2005a). Multi robot trajectory generation for single source explosion parameter estimation. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 2803–2809. Christopoulos, V. and S. Roumeliotis (2005b). Adaptive sensing for instantaneous gas release parameter estimation. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4450–4456. Hoeller, F. and D. Schulz (2007). Accompanying persons with a mobile robot using motion prediction and probabilistic roadmaps. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1260–1265. Jasiobedzki, P., H.-K. Ng, M. Bondy and C.H. McDiarmid (2009). C2SM: a mobile system for detecting and 3D mapping of chemical, radiological, and nuclear contamination. In: Proceedings of Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII. Kathirgamanthan, P., R. McKibbin and R. McLachlan (2002). Source term estimation of pollution from an instantaneous point source. Research Letters in the Information and Mathematical Sciences, 3, pp. 59–67. Neilsen, C.W., D.I. Gertman, D.J. Bruemmer, R.S. Hartley and M.C. Walton (2008). Evaluating robot technologies as tools to explore radiological and other hazardous environments. In: Proceedings of American Nuclear Society Emergency Planning and Response, and Robotics and Security Systems Joint Topical Meeting, Albuquerque, NM, USA. Penzes, S.G. (2006). Multiagent tactical sentry (MATS) project review. In: Proceedings of the International Society for Optical Engineering (SPIE), Kissimmee, FL, USA. St. Louis, R.H., H.H. Hill Jr. and G.A. Eiceman (1990). Ion Mobility Spectrometry in Analytical Chemistry. Critical Reviews in Analytical Chemistry, 21, pp. 321–355. Zarzhitsky, D., D. Spears, W. Spears and D. Thayer (2004). A fluid dynamics approach to multi-robot chemical plume tracing. In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), 3, pp. 1476–1477.
Fig. 8. Schematic overview of the demonstration test run. At first, a reconnaissance unit explores the area, discovering potential NBC threats. Thus, the recon unit is backtracked and the CBRNE robot is deployed. At location A, the robot’s MDS triggers an alert for an artificial gamma source at a range of about 50cm, followed by a more detailed analysis of the identiFinder. After approximately 100s, the radioactive material can be correctly identified. At location B, the LCD sensor almost instantly detects the deployed aerosol, which emulates a dangerous chemical warfare agent (see Fig. 9). The system was also tested with the German NBC Defense School in Sonthofen. The tests showed that most of the requirements were meet and that the hardware reached already quite mature level. Because of these tests, the system will be used as a prototype for a starting procurement.
Fig. 9. The robot encounters the suspicious gas emission at location B. 8. CONCLUSION In this paper, we presented an iteratively evolutionary development of a CBRNE robot system. Within very little time (about 10 months), this robot was built on a COTS wheel-drive platform with in-service sensor systems. It is able to identify different threats like nuclear or chemical 127