協調ロボットにおける環境制約の学習：分散型リーダー・フォロワー手法
Learning Environment Constraints in Collaborative Robotics: A Decentralized Leader-Follower Approach
2台のロボットが障害物のある未知環境で物体を協調搬送するため、明示的通信なしにリーダーがMPCで計画しフォロワーが推定・反応する階層戦略を提案し、役割切替で狭所性能を向上させた。
著者: Monimoy Bujarbaruah, Yvonne R. Stürz, Conrad Holda, Karl H. Johansson, Francesco Borrelli
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
In this paper, we propose a leader-follower hierarchical strategy for two robots collaboratively transporting an object in a partially known environment with obstacles. Both robots sense the local surrounding environment and react to obstacles in their proximity. We consider no explicit communication, so the local environment information and the control actions are not shared between the robots. At any given time step, the leader solves a model predictive control (MPC) problem with its known set of obstacles and plans a feasible trajectory to complete the task. The follower estimates the inputs of the leader and uses a policy to assist the leader while reacting to obstacles in its proximity. The leader infers obstacles in the follower's vicinity by using the difference between the predicted and the real-time estimated follower control action. A method to switch the leader-follower roles is used to improve the control performance in tight environments. The efficacy of our approach is demonstrated with detailed comparisons to two alternative strategies, where it achieves the highest success rate, while completing the task fastest. See the link www.dropbox.com/s/hexadigqkvspaeh/IROS_Video.mp4?dl=0 for a descriptive video of the algorithm.
