Multi-Robot Simultaneous Coverage and Mapping of Complex Scene - Comparison of Different Strategies

Laëtitia Matignon 1, 2, 3 Olivier Simonin 2, 4, 3
1 SMA - Systèmes Multi-Agents
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
3 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : This paper addresses the problem of optimizing the observation of a human scene using several mobile robots. Mobile robots have to cooperate to find a position around the scene maximizing its coverage. The scene coverage is defined as the observation of the human pose skeleton. It is assumed that the robots can communicate but have no map of the environment. Thus the robots have to simultaneously cover and map the scene and the environment. We consider an incremental approach to master state-space complexity. Robots build an hybrid metric-topological map while evaluating the observation of the human pose skeleton. To this end we propose and evaluate different online optimization strategies exploiting local versus global information. We discuss the difference of the performance and cost. Experiments are performed both in simulation and with real robots.
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Laëtitia Matignon, Olivier Simonin. Multi-Robot Simultaneous Coverage and Mapping of Complex Scene - Comparison of Different Strategies. AAMAS 2018 - 17th International Conference on Autonomous Agents and Multiagent Systems - Robotics Track, Jul 2018, Stockholm, Sweden. pp.559-567. ⟨hal-01726120⟩

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