异构机器人协作的Stackelberg策略指导
Stackelberg Strategic Guidance for Heterogeneous Robots Collaboration
AI总结：
本文提出基于Stackelberg博弈的框架，通过计算反馈Stackelberg均衡为单向通信下的异构机器人提供策略指导，提升了多物体重排任务的效率与鲁棒性。
摘要：
本研究探讨了博弈论，特别是Stackelberg博弈的应用，以解决单向通信下异构机器人的有效协调策略生成问题。为此，针对多物体重排任务，我们开发了一个理论与算法框架，通过计算反馈Stackelberg均衡，为一对机械臂（一个领导者和一个跟随者）提供策略指导，其中领导者拥有跟随者决策过程的模型。由于内置了对模型不确定性的容忍度，我们的规划算法生成的策略指导不仅提高了重排任务的求解整体效率，而且对协作中的常见陷阱（例如抖振）具有鲁棒性。
英文摘要：
In this study, we explore the application of game theory, in particular Stackelberg games, to address the issue of effective coordination strategy generation for heterogeneous robots with one-way communication. To that end, focusing on the task of multi-object rearrangement, we develop a theoretical and algorithmic framework that provides strategic guidance for a pair of robot arms, a leader and a follower where the leader has a model of the follower's decision-making process, through the computation of a feedback Stackelberg equilibrium. With built-in tolerance of model uncertainty, the strategic guidance generated by our planning algorithm not only improves the overall efficiency in solving the rearrangement tasks, but is also robust to common pitfalls in collaboration, e.g., chattering.
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