2023/05/19 by Teng Xue, Xue, Teng, Sylvain Calinon +1
Computer Science · Engineering · #Artificial Intelligence in Games #FOS: Computer and information sciences #Human Motion and Animation #Robotic Path Planning Algorithms #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.2305.11835
openalex publication_date 2023/05/19 · openalex created_date 2023/05/23 · openalex updated_date 2026/07/28
Long-term non-prehensile planar manipulation is a challenging task for planning and control, requiring determination of both continuous and discrete contact configurations, such as contact points and modes. This leads to the non-convexity and hybridness of contact optimization. To overcome these difficulties, we propose a novel approach that incorporates human demonstrations into trajectory optimization. We show that our approach effectively handles the hybrid combinatorial nature of the problem, mitigates the issues with local minima present in current state-of-the-art solvers, and requires only a small number of demonstrations while delivering robust generalization performance. We validate our results in simulation and demonstrate its applicability on a pusher-slider system with a real Franka Emika robot.