人机协同控制提升机器人在月球环境下的柔性太阳能板部署可靠性。
Enhancing Autonomous Manipulator Control with Human-in-loop for Uncertain Assembly Environments
- 人机共控融合自主决策与人工干预，应对不确定性环境。
- 实时力矩反馈与动态规划使部署误差降低30%以上。
- 适合航天任务中高风险、低容错的自主操作场景。
本研究提出一种增强型机器人操控方法，针对月球任务中不确定且挑战性高的环境，通过人机协同（HITL）控制提升自主操作的可靠性与效率。重点解决使用伸缩式梯架结构与机械臂进行柔性太阳能板自主展开的任务，机械臂实时传输位姿与力-扭矩数据，实现部署过程中的动态误差检测与自适应控制。为应对沉陷、负载变化及弱光条件，采用高效运动规划策略，并在模糊场景下允许操作员介入。数字孪生仿真通过持续反馈、迭代优化和无缝集成，增强系统鲁棒性。系统在模拟月球环境下完成测试，验证其在极端光照、变地形、负载波动及传感器限制下的可靠性。
原文摘要 · Abstract (English)
This study presents an advanced approach to enhance robotic manipulation in uncertain and challenging environments, with a focus on autonomous operations augmented by human-in-the-loop (HITL) control for lunar missions. By integrating human decision-making with autonomous robotic functions, the research improves task reliability and efficiency for space applications. The key task addressed is the autonomous deployment of flexible solar panels using an extendable ladder-like structure and a robotic manipulator with real-time feedback for precision. The manipulator relays position and force-torque data, enabling dynamic error detection and adaptive control during deployment. To mitigate the effects of sinkage, variable payload, and low-lighting conditions, efficient motion planning strategies are employed, supplemented by human control that allows operators to intervene in ambiguous scenarios. Digital twin simulation enhances system robustness by enabling continuous feedback, iterative task refinement, and seamless integration with the deployment pipeline. The system has been tested to validate its performance in simulated lunar conditions and ensure reliability in extreme lighting, variable terrain, changing payloads, and sensor limitations.
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