On Combining Multi-robot Coverage and Reciprocal Collision Avoidance
Although robotic coverage and collision avoidance are active areas of robotics research, the avoidance of collision situations between robots has often been neglected in the context of multi-robot coverage tasks. In fact, for robots of physical size, collisions are likely to happen during deployment and coverage in densely packed multi-robot configurations. For this reason, we aim to motivate by this paper the combined use of multi-robot coverage and reciprocal collision avoidance. We present a taxonomy of collision scenarios in multi-robot coverage problems. In particular, coverage tasks with built-in heterogeneity such as multiple antagonistic objectives or robot constraints are shown to benefit from the combination. Based on our taxonomy, we evaluate four representative robotic use cases in simulation by combining the specific methods of Voronoi coverage and reciprocal velocity obstacles.
KeywordsMulti-robot coverage Voronoi tessellation Reciprocal collision avoidance Velocity obstacles Taxonomy of collision scenarios Evaluation of use cases
The work presented in this paper has been carried out at the Distributed Intelligent Systems and Algorithms Laboratory at EPFL. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007–2013—Challenge 2—Cognitive Systems, Interaction, Robotics—under grant agreement No 601033—MOnarCH.
- 2.Gage, D.W.: Command control for many-robot systems. In Proceedings of the Annual AUVS Technical Symposium, vol. 10, pp. 28–34 (1992)Google Scholar
- 5.Pimenta, L.C.A., Kumar, V., Mesquita, R.C., Pereira, G.A.S.: Sensing and coverage for a network of heterogeneous robots. In Proceedings of the IEEE Conference on Decision and Control, pp. 3947–3952 (2008)Google Scholar
- 7.Parker, L.E.: Distributed intelligence: overview of the field and its application in multi-robot systems. J. Phys. Agents 2(2), 5–14 (2008)Google Scholar
- 8.Breitenmoser, A.: Multi-robot coverage and path planning for the inspection of curved surfaces, Ph.D. dissertation, no. 21009, ETH Zurich (2013)Google Scholar
- 9.van den Berg, J., Lin, M.C., Manocha, D.: Reciprocal velocity obstacles for real-time multi-agent navigation, In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1928–1935 (2008)Google Scholar
- 10.van den Berg, J., Guy, S.J., Lin, M.C., Manocha, D.: Reciprocal n-body collision avoidance. In: Proceedings of the 14th International Symposium on Robotics Research, STAR, vol. 70, pp. 3–19 (2011)Google Scholar
- 11.Alonso-Mora, J., Breitenmoser, A., Rufli, M., Beardsley, P., Siegwart, R.: Optimal reciprocal collision avoidance for multiple non-holonomic robots. In: Proceedings of the 10th International Symposium on Distributed Autonomous Robotic Systems, STAR, vol. 83, pp. 203–216 (2013)Google Scholar
- 12.Alonso-Mora, J., Breitenmoser, A., Beardsley, P., Siegwart, R.: Reciprocal collision avoidance for multiple car-like robots, In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 360–366 (2012)Google Scholar
- 13.Tan, J., Xi, N., Sheng, W., Xiao, J.: Modeling multiple robot systems for area coverage and cooperation. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2568–2573 (2004)Google Scholar
- 14.Santos, V.G., Campos, M.F.M., Chaimowicz, L.: On segregative behaviors using flocking and velocity obstacles. In: Proceedings of the 11th International Symposium on Distributed Autonomous Robotic Systems, STAR, vol. 104, pp. 121–133 (2014)Google Scholar
- 15.He, L., van den Berg, J.: Meso-scale planning for multi-agent navigation. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2824–2829 (2013)Google Scholar
- 16.Derenick, J., Michael, N., Kumar, V.: Energy-aware coverage control with docking for robot teams. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3667–3672 (2011)Google Scholar