发表机构
KTH Royal Institute of Technology; Seoul National University（瑞典皇家理工学院; 首尔大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一种安全关键控制框架，利用CLF和CBF约束的混合整数推力分配，使追踪机器人通过单向推挤在微重力下协同运输被动目标，实现参考跟踪和避障，并经Gazebo仿真验证。
AI 中文摘要
我们提出一个安全关键框架，用于微重力下被动目标物的协同运输，其中一组追踪机器人通过单向推挤接触来跟踪人类提供的期望扭转，同时确保目标运动安全。纯推挤交互特性引入了稀疏、构型相关的执行约束，要求追踪机器人在期望推挤分配变化时物理上重新定位到目标体上。为应对这些挑战，我们构建了一个延迟感知的反馈控制架构，利用控制李雅普诺夫函数（CLF）和控制障碍函数（CBF）约束，在混合整数推力分配程序中分别确保目标的稳定性和安全性。所提框架能够在间歇性控制权限下，实现对参考轨迹的跟踪，并保证对圆形障碍物的避障，为空间环境中人类监督的协同运输自由飞行器奠定了基础。该框架通过Gazebo仿真进行了验证。
英文摘要
We propose a safety-critical framework for the cooperative transportation of passive targets in microgravity, where a team of chaser robots acts through unilateral pushing contacts to track a human-provided desired twist while ensuring safe target motion. The pushing-only nature of the interaction introduces sparse, configuration-dependent actuation constraints requiring chasers to physically relocate on the target body when the desired pushing allocation changes. To address these challenges, we formulate a delay-aware feedback control architecture leveraging Control Lyapunov Function (CLF) and Control Barrier Function (CBF) constraints within a mixed-integer thrust allocation program to enforce stability and safety of the target, respectively. The proposed framework enables reference tracking while guaranteeing obstacle avoidance with a circular obstacle despite intermittent control authority, providing a foundation for human-supervised cooperative transportation of free-flyers in space environments. The proposed framework is validated through Gazebo simulations.
