Human-Aware Motion Planning for Mobile Robots in Social Encounters

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This video presents the implicitly coordinated motion model (ICMM), a novel motion model for the prediction, planning and coordination of agent trajectories in multi-agent encounters.
It explicitly incorporates the social cooperation between humans and mobile robots. Parameters of the ICMM are identified from recorded actual encounters among groups of humans using methods from inverse optimal control.

The agents’ trajectories are optimized using the Timed-Elastic-Band framework [1,2] considering multiple conflicting objectives such as fastest path, minimal spatial separtion among agents, (kino-)dynamic constraints but also global proxemic aspects such as coherent motion of social groups and a prefered side of passing each other.

The recorded dataset contains 73 recorded encounters with up to five humans and a total of 283 individual trajectories.

Technical note: the program running in this video has been compiled in debug mode. Compilation with release settings results in a speedup factor of 7.

Time-line:
00:09 Parallel trajectory optimization in alternative homotopy classes
00:50 Parallel trajectory optimization with dynamic homotopy class exploration
01:37 TEB selection and implictly coordinated motion model (ICMM)
02:24 Simulations of social encounters
04:11 Using the ICMM on a mobile robot

[1] Rösmann, C., W. Feiten, T. Wösch, F. Hoffmann und T. Bertram: Trajectory Modification Considering Dynamic Constraints of Autonomous Robots, 7th German Conference on Robotics, Munich, May 2012
[2] Rösmann, C., W. Feiten, T. Wösch, F. Hoffmann und T. Bertram: Efficient Trajectory Optimization using a Sparse Model, 6th European Conference on Mobile Robots, Barcelona, 2013

The Institute of Control Theory and Systems Engineering (RST) at TU Dortmund is engaged in fundamental research in the fields of robotics and computational intelligence. Furthermore the applied research focus is automotive systems and mechatronics. //www.rst.e-technik.tu-dortmund.de

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