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3-D relative positioning sensor for indoor flying robots

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Abstract

Swarms of indoor flying robots are promising for many applications, including searching tasks in collapsing buildings, or mobile surveillance and monitoring tasks in complex man-made structures. For tasks that employ several flying robots, spatial-coordination between robots is essential for achieving collective operation. However, there is a lack of on-board sensors capable of sensing the highly-dynamic 3-D trajectories required for spatial-coordination of small indoor flying robots. Existing sensing methods typically utilise complex SLAM based approaches, or absolute positioning obtained from off-board tracking sensors, which is not practical for real-world operation. This paper presents an adaptable, embedded infrared based 3-D relative positioning sensor that also operates as a proximity sensor, which is designed to enable inter-robot spatial-coordination and goal-directed flight. This practical approach is robust to varying indoor environmental illumination conditions and is computationally simple.

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Notes

  1. http://www.vishay.com (BPV22NF, accessed Feb. 2011).

  2. http://www.vishay.com (TSAL4400, accessed Feb. 2011).

  3. Video: http://jfroberts.com/phd (Sensor calibration).

  4. Video: http://jfroberts.com/phd (Sensor characterisation).

  5. Video: http://jfroberts.com/phd (Eye-bot tracking).

  6. http://jfroberts.com/phd (Eye-bot hovering collision).

  7. Video: http://jfroberts.com/phd (Eye-bot scenario).

References

  • Achtelik, M., Bachrach, A., He, R., Prentice, S., & Roy, N. (2009). Stereo vision and laser odometry for autonomous helicopters in GPS-denied indoor environments. In Proceedings of unamanned systems technology XI (SPIE’09), Orlando (Vol. 7332, pp. 1901–1910). Bellingham: The International Society for Optical Engineering.

    Google Scholar 

  • Bachrach, A., He, R., & Roy, N. (2009). Autonomous flight in unstructured and unknown indoor environments. In Proceedings of the 2009 European micro air vehicle conference and flight competition (EMAV’09).

    Google Scholar 

  • Blösch, M., Weiss, S., Scaramuzza, D., & Siegwart, R. (2010). Vision based mav navigation in unknown and unstructured environments. In 2010 IEEE international conference on robotics and automation (ICRA) (pp. 21–28).

    Chapter  Google Scholar 

  • Bonani, M., Longchamp, V., Magnenat, S., Rétornaz, P., Burnier, D., Roulet, G., Vaussard, F., Bleuler, H., & Mondada, F. (2010). The MarXbot, a miniature mobile robot opening new perspectives for the collective-robotic research. In International conference on intelligent robots and systems (IROS), 2010 IEEE/RSJ (pp. 4187–4193). New York: IEEE Press.

    Chapter  Google Scholar 

  • Breitenmoser, A., Kneip, L., & Siegwart, R. (2011). A monocular vision-based system for 6d relative robot localization. In Proc. of the IEEE/RSJ international conference on intelligent robots and systems (IROS).

    Google Scholar 

  • Grzonka, S., Grisetti, G., & Burgard, W. (2009). Towards a navigation system for autonomous indoor flying. In Proceedings of the international conference on robotics and automation (ICRA’09) (pp. 2878–2883). Piscataway: IEEE Press.

    Google Scholar 

  • Guenard, N., Hamel, T., & Mahony, R. (2008). A practical visual servo control for a unmanned aerial vehicle. IEEE Transactions on Robotics and Automation, 24(2), 331–341.

    Google Scholar 

  • Hoffmann, G. M., & Tomlin, C. J. (2008). Decentralized cooperative collision avoidance for acceleration constrained vehicles. In Proceedings of the 47th IEEE conference on decision and control, Cancun, Mexico.

    Google Scholar 

  • Kelly, I. D., & Keating, D. D. A. (1996). Flocking by the fusion of sonar and active infrared sensors on physical autonomous mobile robots. In Proc. of the third int. conf. on mechatronics and machine vision in practice (pp. 1–4).

    Google Scholar 

  • Kemppainen, A., Haverinen, J., & Roning, J. (2006). An infrared location system for relative pose estimation of robots. In Symposium of robot design, dynamics, and control (pp. 379–386).

    Google Scholar 

  • Kirchner, N., & Furukawa, T. (2005). Abstract infrared localisation for indoor uavs. In Proceedings of the international conference on sensing technology (pp. 60–65).

    Google Scholar 

  • Lander, C.-W. (1993). Rectifying circuits. In Power electronics (3rd ed.). New York: McGraw Hill.

    Google Scholar 

  • Lupashin, S., Schöllig, A., Sherback, M., & D’Andrea, R. (2010). A simple learning strategy for high-speed quadrocopter multi-flips. In Proceedings of the international conference on robotics and automation (ICRA’10) (pp. 642–648). Piscataway: IEEE Press.

    Google Scholar 

  • McLurkin, J., & Smith, J. (2004). Distributed algorithms for dispersion in indoor environments using a swarm of autonomous mobile robots. In 7th international symposium on distributed autonomous robotic systems, Toulouse, France.

    Google Scholar 

  • Melhuish, C., & Welsby, J. (2002). Gradient ascent with a group of minimalist real robots: Implementing secondary swarming. In IEEE international conference on systems, man and cybernetics (Vol. 2, pp. 509–514).

    Google Scholar 

  • Montesano, L., Montano, L., & Burgard, W. (2004). Relative localization for pairs of robots based on unidentifiable moving features. In Proceedings 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS 2004) (Vol. 2, pp. 1537–1543).

    Google Scholar 

  • Naboulsi, M., Sizun, H., & Fornel, F. (2005). Propagation of optical and infrared waves in the atmosphere. In Proceedings of the union radio scientifique internationale.

    Google Scholar 

  • Nakamura, T., Oohara, M., Ogasawara, T., & Ishiguro, H. (2003). Fast self-localization method for mobile robots using multiple omnidirectional vision sensors. Machine Vision and Applications, 14(2), 129–138.

    Google Scholar 

  • Pilz, U., Popov, A., & Werner, H. (2009). Robust controller design for formation flight of quad-rotor helicopters. In Proceedings of the 48th IEEE conference on decision and control, held jointly with the 2009 28th Chinese control conference. CDC/CCC 2009 (pp. 8322–8327).

    Google Scholar 

  • Pugh, J., Raemy, X., Favre, C., Falconi, R., & Martinoli, A. (2009). A fast on-board relative positioning module for multi-robot systems. In IEEE/ASME transactions on mechatronics, focused section on mechatronics in multi robot systems.

    Google Scholar 

  • Rivard, F., Bisson, J., Michaud, F., & Letourneau, D. (2008). Ultrasonic relative positioning for multi-robot systems. In IEEE international conference on robotics and automation, ICRA 2008 (pp. 323–328).

    Chapter  Google Scholar 

  • Roberts, J., Zufferey, J.-C., & Floreano, D. (2008). Energy management for indoor hovering robots. In Proceedings of the international conference on intelligent robots and systems (IROS’08) (pp. 1242–1247). Piscataway: IEEE Press.

    Google Scholar 

  • Roberts, J., Stirling, T., Zufferey, J.-C., & Floreano, D. (2009). 2.5D infrared range and bearing system for collective robotics. In Proceedings of the international conference on intelligent robots and systems (IROS’09) (pp. 3659–3664). Piscataway: IEEE Press.

    Chapter  Google Scholar 

  • Rudol, P., Wzorek, M., Conte, G., & Doherty, P. (2008). Micro unmanned aerial vehicle visual servoing for cooperative indoor exploration. In Proceedings of the aerospace conference (pp. 1–10). Piscataway: IEEE Press.

    Google Scholar 

  • Sahin, E. (2005). Swarm robotics: from sources of inspiration to domains of application. In International workshop on swarm robotics (pp. 10–20).

    Chapter  Google Scholar 

  • Shen, S., Michael, N., & Kumar, V. (2011). Autonomous multi-floor indoor navigation with a computationally constrained mav. In Proc. of the IEEE international conference on robotics and automation (ICRA).

    Google Scholar 

  • Shoval, S., & Borenstein, J. (2001). Measuring the relative position and orientation between two mobile robot with binaural sonar. In ANS 9th international topical meeting on robotics and remote systems, Seattle, Washington.

    Google Scholar 

  • Soundararaj, S. P., Sujeeth, A. K., & Saxena, A. (2009). Autonomous indoor helicopter flight using a single onboard camera. In Proceedings of the 2009 IEEE/RSJ international conference on intelligent robots and systems, IROS’09 (pp. 5307–5314). Piscataway: IEEE Press.

    Chapter  Google Scholar 

  • Stirling, T., Wischmann, S., & Floreano, D. (2010). Energy-efficient indoor search by swarms of simulated flying robots without global information. Swarm Intelligence, 4(2), 117–143.

    Article  Google Scholar 

  • Valenti, M., Bethke, B., How, J.-P., Farias, D.-P., & Vian, J. (2007). Embedding health management into mission tasking for UAV teams. In American control conference (pp. 5777–5783). Piscataway: IEEE Press.

    Chapter  Google Scholar 

  • Weiss, S., Scaramuzza, D., & Siegwart, R. (2011). Monocular-slam–based navigation for autonomous micro helicopters in gps-denied environments. Journal of Field Robotics, 28(6), 854–874.

    Article  Google Scholar 

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Acknowledgements

We would like to thank the people who assisted with the automated calibration system and fabrication of ten 3-D sensor rings: IRIDIA, Université Libre de Bruxelles; Ali Emre Turgut, Arne Brutschy, Manuele Brambilla, Nithin Mathews. LIS, Ecole Polytechnique Fédérale de Lausanne (EPFL); Thomas Schaffter, Peter Dürr, Jürg Germann, Yannick Gasser, Michal Dobrzynski, Yannick Gasser. We would also like to thank Michael Bonani and Philippe Rétornaz for providing valuable feedback during the design phase. Finally, we would like to thank the following people for providing the ABB robot, wheeled robot and mechanical interface: LRSO, EPFL; Lionel Flaction, Tarek Baaboura, Prof. Reymond Clavel, Dr. Francesco Mondada. This work is part of the Swarmanoid project, Future Emerging Technologies (FET IST-022888), funded by the European commission. Additional funding has also come from the Swiss National Science Foundation.

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Correspondence to James F. Roberts.

Additional information

J.F.R. developed the concept of relative positioning sensing for enabling goal-directed flight on indoor collective flying robots, wrote the manuscript, developed the sensor hardware/firmware, developed the calibration tools and characterised the sensor.

T.S. extensively contributed to the sensor firmware and characterisation.

J.-C.Z. and D.F. conceived and directed the project sponsoring the work described in the article. They also provided continue support and feedback towards reaching the attained results.

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Roberts, J.F., Stirling, T., Zufferey, JC. et al. 3-D relative positioning sensor for indoor flying robots. Auton Robot 33, 5–20 (2012). https://doi.org/10.1007/s10514-012-9277-0

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