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Heterogeneous Teams of Modular Robots for Mapping and Exploration

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Abstract

In this article, we present the design of a team of heterogeneous, centimeter-scale robots that collaborate to map and explore unknown environments. The robots, called Millibots, are configured from modular components that include sonar and IR sensors, camera, communication, computation, and mobility modules. Robots with different configurations use their special capabilities collaboratively to accomplish a given task. For mapping and exploration with multiple robots, it is critical to know the relative positions of each robot with respect to the others. We have developed a novel localization system that uses sonar-based distance measurements to determine the positions of all the robots in the group. With their positions known, we use an occupancy grid Bayesian mapping algorithm to combine the sensor data from multiple robots with different sensing modalities. Finally, we present the results of several mapping experiments conducted by a user-guided team of five robots operating in a room containing multiple obstacles.

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References

  • Arkin, R.C. and Balch, T.R. 1998. In Cooperative Multiagent Robotic Systems AI-based Mobile Robots: Case Studies of Successful Robot Systems, D. Kortenkamp, R.P. Bonasso, and R. Murphy (Eds.), MIT Press.

  • Atiya, S. and Hager, G. 1993. Real-time vision-based robot localization. IEEE Transactions on Robotics and Automation, 9(6):785–800.

    Google Scholar 

  • Borenstein, J., Everett, H.R., and Feng, L. 1996. Navigating Mobile Robots: Sensors and Techniques, A.K. Peters, Ltd.: Wellesley, MA.

    Google Scholar 

  • Brooks, R.A. 1986. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, RA-2(1): 14–23.

    Google Scholar 

  • Conticelli, F. and Khosla, P.K. 1999. Image-based visual control of nonholonomic mobile robots. Technical Report, ICES04-05-99, The Institute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA 15213.

    Google Scholar 

  • Diehl, P.D., Saptharishi, M., Hampshire, J.B., and Khosla, P.K. 1999. Collaborative surveillance using both fixed and mobile unattended ground sensor platforms. In SPIE's 13th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls (AeroSense), Marriott's OrlandoWorld Center, Orlando, Florida, USA.

    Google Scholar 

  • Dixon, K., Dolan, J., Huang,W., Paredis, C., Khosla, P. 1999. RAVE: A real and virtual environment for multiple mobile robot systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99), Kyongju, Korea.

  • Dixon, K.R., Pham, T.Q., and Khosla, P.K. 2000. Port-based adaptable agent architecture. In Proceedings of the International Workshop on Self-adaptive Software. Oxford, UK, April 17–19.

  • Dolan, J.M., Trebi-Ollennu, A., Soto, A., and Khosla, P.K. 1999. Distributed tactical surveillance with ATVs. In SPIE's 13th Annual International Symposium on Aerospace/Defense Sensing, Simulation, and Controls (AeroSense), Marriott's OrlandoWorld Center, Orlando, Florida, USA.

    Google Scholar 

  • Elfes, A. 1989. Occupancy grids: A probabilistic framework for mobile robot perception and navigation. Ph.D. Thesis, Department of Electrical and Computer Engineering, Carnegie Mellon University.

  • Fletcher, R. 1987. Practical Methods of Optimization, 2nd Ed., J. Wiley & Sons, Ltd.: New York, NJ.

    Google Scholar 

  • Getting, I.A. 1993. The Global Positioning System. IEEE Spectrum, pp. 36–47.

  • Hollis, R. 1996. Whither microbots? In Proc.7th.Int'l.Conf.On Micromachine and Human Science (MHS' 96), Nagoya, Japan.

  • ISR—IS Robotics, Inc. 1994. RR-1/BS-1 system for communications and positioning—preliminary data sheet. IS Robotics, Twin City Office Center, Suite 6, 22 McGrath Highway, Somerville, MA 02143, 617-629-0055.

  • Jenkin, M., Milios, E., Jasiobedzki, P., Bains, N., and Tran, K. 1993. Global navigation for ARK. In Proceedings of the 1993 IEEE/RSJ International Conference on Intelligent Robotics and Systems, Yokohama, Japan, pp. 2165–2171.

  • Kleeman, L. 1992. Optimal estimation of position and heading for mobile robots using ultrasonic beacons and dead-reckoning. In Proceedings of the 1992 IEEE International Conference on Robotics and Automation, May, Nice, France, pp. 2582–2587.

  • Lekei, D., 1997. Using a PIC16C5X as a smart I2C Peripheral. AN541, Microchip Technology, Inc. Chandler, AZ.

  • Leonard, J.F. and Durrant-Whyte, H.F. 1991. Mobile robot localization by tracking geometric beacons. IEEE Transactions on Robotics and Automation. 7(3):376–382.

    Google Scholar 

  • Mataric, M. 1995. Issues and approaches in the design of collective autonomous agents. Robotics and Autonomous Systems, 16(2–4):321–331.

    Google Scholar 

  • McLurkin, J.D. 1996. Using cooperative robots for explosive ordnance disposal. Technical Document, Massachusetts Institute of Technology, Artificial Intelligence Laboratory, Cambridge, MA, USA 02139.

  • Mondada, F., Franzi, E., and Ienne, P. 1993. Mobile robot miniaturization: A tool for investigation in control algorithms. In ISER'93, Kyoto, Japan.

  • Moravec, H.P. 1988. Sensor fusion in evidence grids for mobile robots. AI Magazine, pp. 61–74.

  • Navarro-Serment, L.E., Paredis, C.J.J., and Khosla, P.K. 1999. A beacon system for the localization of distributed robotic teams. In Proceedings of the International Conference on Field and Service Robotics, Pittsburgh, PA.

  • Parker, L.E. 1999. Adaptive heterogeneous multi-robot teams. (Neurocomputing, special issue of NEURAP' 98) Neural Networks and Their Applications, 28:75–92.

    Google Scholar 

  • Rus, D., Donald, B.R., and Jennings, J. 1995. Moving furniture with teams of autonomous mobile robots. In Proc.IEEE/Robotics Society of Japan InternationalWorkshop on Intelligent Robots and Systems, (IROS), Pittsburgh, PA.

  • Salido, J., Paredis, C.J.J., and Khosla, P.K. 1999. Continuous probabilistic mapping by autonomous robots. In Proceedings of the International Symposium on Experimental Robotics. Sydney, Australia, March 26–28.

  • Stuck, E.R., Manz, A., Green, D.A., and Elgazzar, S. 1994. Map updating and path planning for real-time mobile robot navigation. In 1994 International Conference on Intelligent Robots and Systems (IROS' 94), Munich, Germany, pp. 753–760.

  • Thrun, S. 1998. Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence, 99(1):21–71.

    Google Scholar 

  • Veloso, M., Stone, P., Han, K., and Achim, S. 1998. The CMUnited-97 small robot team. In Proceedings of RoboCup-97: The First Robot World Cup Soccer Games and Conferences, H. Kitano (Ed.), Springer Verlag: Berlin.

    Google Scholar 

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Grabowski, R., Navarro-Serment, L.E., Paredis, C.J. et al. Heterogeneous Teams of Modular Robots for Mapping and Exploration. Autonomous Robots 8, 293–308 (2000). https://doi.org/10.1023/A:1008933826411

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