通过帧间相关性实现动态目标的平稳空间机械臂操作
Learning Smooth and Robust Space Robotic Manipulation of Dynamic Target via Inter-frame Correlation
- 利用历史帧与当前帧的时序相关性捕捉运动特征
- 在地面模拟微重力环境下实现稳定平滑轨迹控制
- 适合航天在轨服务中动态非合作目标抓取任务
在轨服务是未来航空航天工程的关键前沿，对动态非合作目标的操控技术尤为关键。在微重力环境下，物体通常自由漂浮，缺乏地球上的支撑与摩擦约束，极大增加了空间机器人操作的复杂性。传统基于规划与控制的方法主要适用于已知静态场景，实时响应能力不足。为实现在未知、非结构化太空环境中对动态目标的精确操控，本文提出一种融合历史时序信息与帧间相关性的数据驱动方法。通过挖掘历史帧与当前帧之间的时序相关性，系统可有效捕捉场景中的运动特征，从而生成稳定平滑的操作轨迹。为验证所提方法的有效性，构建了一个包含PIPER X机械臂和双轴直线导轨的地面实验平台，可精确模拟二维平面内的微重力自由漂浮运动。
原文摘要 · Abstract (English)
On-orbit servicing represents a critical frontier in future aerospace engineering, with the manipulation of dynamic non-cooperative targets serving as a key technology. In microgravity environments, objects are typically free-floating, lacking the support and frictional constraints found on Earth, which significantly escalates the complexity of tasks involving space robotic manipulation. Conventional planning and control-based methods are primarily limited to known, static scenarios and lack real-time responsiveness. To achieve precise robotic manipulation of dynamic targets in unknown and unstructured space environments, this letter proposes a data-driven space robotic manipulation approach that integrates historical temporal information and inter-frame correlation mechanisms. By exploiting the temporal correlation between historical and current frames, the system can effectively capture motion features within the scene, thereby producing stable and smooth manipulation trajectories for dynamic targets. To validate the effectiveness of the proposed method, we developed a ground-based experimental platform consisting of a PIPER X robotic arm and a dual-axis linear stage, which accurately simulates micro-gravity free-floating motion in a 2D plane.
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