密度驱动的非完整多机器人系统安全覆盖控制

中文摘要 AI 辅助

密度驱动最优控制（D2OC）提供了一种将多机器人团队分布到非均匀空间分布上的原则性方法。然而，将D2OC应用于非完整机器人时，在参考运动上施加的安全约束与决定实际机器人运动的物理输入之间产生了差距。我们通过直接在机器人物理输入上强制执行安全约束，同时保留密度驱动的覆盖目标来解决这一问题。所提出的框架通过反馈线性化前视点将D2OC与控制屏障函数安全滤波器相结合，使得在控制过程中能够同时考虑安全性和执行器限制。我们进一步推导了一个安全裕度，该裕度考虑了每个控制间隔内的前视几何、机器人足迹和运动。仿真结果表明，所提出的方法在保持所需物理间距的同时，实现了与传统参考跟踪方法相当的覆盖性能，而传统方法虽能在参考运动上满足安全性，却可能违反相应的物理间隙。在Robotarium中多个非完整机器人上的实验进一步证明了在驱动机器人朝向期望空间分布的同时实现安全执行。这些结果表明，直接在物理输入上强制执行安全性可以消除密度驱动多机器人覆盖中安全认证与物理机器人运动之间的不匹配。

英文摘要

Density-Driven Optimal Control (D2OC) provides a principled approach to distributing multi-robot teams over non-uniform spatial distributions. Applying D2OC to nonholonomic robots, however, creates a gap between safety constraints imposed on a reference motion and the physical inputs that determine the actual robot motion. We address this issue by enforcing the safety constraint directly on the robot's physical inputs while preserving the density-driven coverage objective. The proposed framework combines D2OC with a control barrier function safety filter through a feedback-linearizing look-ahead point, allowing safety and actuator limits to be considered together during control. We further derive a safety margin that accounts for the look-ahead geometry, robot footprint, and motion during each control interval. Simulation results show that the proposed method maintains the required physical separation while achieving coverage performance comparable to a conventional reference-tracking approach, which can satisfy safety on the reference motion yet violate the corresponding physical clearance. Experiments on multiple nonholonomic robots in the Robotarium further demonstrate safe execution while driving the robots toward the desired spatial distribution. These results show that enforcing safety directly on the physical inputs can eliminate the mismatch between safety certification and physical robot motion in density-driven multi-robot coverage.

发表机构

• Texas Tech University（德克萨斯理工大学）

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