arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2109.07673eess.SYcs.MAcs.ROcs.SY
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回到未来:高效,时间一致的解决方案在达到避免游戏

Back to the Future: Efficient, Time-Consistent Solutions in Reach-Avoid Games

Princeton University(普林斯顿大学);UT Austin(德克萨斯大学奥斯汀分校)

Dennis R. Anthony, Duy P. Nguyen, David Fridovich-Keil, Jaime F. Fisac

摘要:

我们研究了一类达到避免动态游戏中,多个代理相互作用非合作,每个人都希望满足一个不同的目标标准,同时避免失败的标准。到达-避免游戏通常用于表达移动机器人运动规划中的安全关键最优控制问题。在这里,我们专注于寻找时间一致的解决方案,即使机器人早期偏离计划,未来的运动计划仍然是最佳的,例如,内在动态不确定性或外在环境干扰。我们的主要贡献是一个计算效率高的算法,多智能体达到避免游戏,使时间一致的解决方案,为所有的球员。我们证明了我们的方法在两个和三个球员模拟驾驶的情况下,我们的方法为所有代理提供安全的控制策略。

英文摘要:

We study the class of reach-avoid dynamic games in which multiple agents interact noncooperatively, and each wishes to satisfy a distinct target criterion while avoiding a failure criterion. Reach-avoid games are commonly used to express safety-critical optimal control problems found in mobile robot motion planning. Here, we focus on finding time-consistent solutions, in which future motion plans remain optimal even when a robot diverges from the plan early on due to, e.g., intrinsic dynamic uncertainty or extrinsic environment disturbances. Our main contribution is a computationally-efficient algorithm for multi-agent reach-avoid games which renders time-consistent solutions for all players. We demonstrate our approach in two- and three-player simulated driving scenarios, in which our method provides safe control strategies for all agents.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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