用博弈论方法提升在线运动规划的安全性与计算效率
Captivity-Escape Games as a Means for Safety in Online Motion Generation
- 构建捕获-逃脱零和微分博弈，动态调整规划模型性能
- 计算速度比现有方法快数个数量级，数值精度更高
- 适合需要实时安全控制的机器人或自动驾驶系统
本文针对现有基于模型的在线运动生成方法在安全性保障中存在保守性高、数值精度低及计算开销大的问题，提出一种新颖的捕获-逃脱零和微分博弈方法。该方法通过自适应调整规划模型性能，使生成的参考轨迹能在预设安全裕度内被联合设计的安全控制器准确跟踪。数值实验表明，相比当前最先进方法，该方法在计算速度上实现数量级提升，同时显著改善了数值精度。
原文摘要 · Abstract (English)
This paper addresses conservatism, limited numerical accuracy, and high computational effort in existing methods ensuring safety by design in online model-based motion generation. The presented method employs a novel captivity-escape zero-sum differential game to adapt the planning model's performance so that resulting reference trajectories are trackable within a prescribed safety margin by a jointly synthesized safety controller. A numerical example demonstrates orders-of-magnitude faster computation and improved numerical accuracy compared to the state of the art.
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