Safe tracking control for free-flying space robots via control barrier functions

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2024-11-21 DOI:10.1016/j.robot.2024.104865

Chengrui Shi , Tao Meng , Kun Wang , Jiakun Lei , Weijia Wang , Renhao Mao

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引用次数: 0

Abstract

Safety is a critical problem for space robots in future complex autonomous On-Orbit Services. In this paper, we propose a real-time and guaranteed method for whole-body safe tracking control of free-flying space robots using High Order Control Barrier Functions (HOCBFs).

We start by utilizing capsule-shaped safety envelopes for an accurate approximation of space robots. This is followed by the development of HOCBF-based safety filters to ensure simultaneous collision avoidance and compliance with specified joint limits. To mitigate feasibility issues, we incorporate the optimal decay method into our safety filter design. Furthermore, we introduce a data-driven re-planning mechanism to avoid local minimums of control barrier functions. Such a mechanism primarily operates through anomaly detection of tracking behavior using One-Class Support Vector Machines.

Numerical experiments demonstrate that our method effectively ensures safety of space robots under complicated circumstances without compromising the system’s ability to achieve its intended goals.

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通过控制屏障功能实现自由飞行太空机器人的安全跟踪控制

在未来复杂的自主在轨服务中，安全是太空机器人面临的一个关键问题。在本文中，我们提出了一种使用高阶控制障碍函数（HOCBFs）对自由飞行的太空机器人进行全身安全跟踪控制的实时和有保证的方法。随后，我们开发了基于 HOCBF 的安全滤波器，以确保同时避免碰撞和遵守指定的关节限制。为了缓解可行性问题，我们在安全滤波器设计中采用了最优衰减法。此外，我们还引入了数据驱动的重新规划机制，以避免控制障碍函数的局部最小值。数值实验证明，我们的方法能有效确保太空机器人在复杂环境下的安全，同时不影响系统实现预期目标的能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.