机器人可实时识别柔性约束并安全操作未知环境中的弹性物体
Characterization of Constraints in Flexible Unknown Environments
- 基于局部力与位置信息在线探索约束
- 实时识别柔性铰链等常见约束类型及螺栓参数
- 适用于手术中器官牵拉等需安全协作的场景
本文提出一种在线路径规划算法，实现机器人在未知环境中对柔性约束物体的安全自主操作。通过实时识别与表征感知到的柔性约束及系统全局刚度，该方法使机器人能同步完成探索、表征与操作。无需先验知识，利用基于局部力与位置信息的约束探索实现导航。在物体轨迹上多姿态下分析约束刚度，并结合刚度特征向量，通过简单机械约束（如铰链、平面约束）的图谱识别全局刚度行为。算法经仿真与实验验证，成功实现实时识别多种常见简单机械约束（如柔性铰链）并获取相关螺旋参数。结果表明，该方法具备同时进行全局约束/刚度探索与安全操作的可行性，有望应用于手术中器官牵拉与操作等安全协作场景。
原文摘要 · Abstract (English)
This paper presents an online path planning algorithm for safe autonomous manipulation of a flexibly constrained object in an unknown environment. Methods for real time identification and characterization of perceived flexible constraints and global stiffness are presented. Used in tandem, these methods allow a robot to simultaneously explore, characterize, and manipulate an elastic system safely. Navigation without a-priori knowledge of the system is achieved using constraint exploration based on local force and position information. The perceived constraint stiffness is considered at multiple poses along an object's (system) trajectory. Using stiffness eigenvector information, global stiffness behavior is characterized and identified using an atlas of simple mechanical constraints, such as hinges and planar constraints. Validation of these algorithms is carried out by simulation and experimentally. The ability to recognize several common simple mechanical constraints (such as a flexible hinge) in real time, and to subsequently identify relevant screw parameters is demonstrated. These results suggest the feasibility of simultaneous global constrain/stiffness exploration and safe manipulation of flexibly constrained objects. We believe that this approach will eventually enable safe cooperative manipulation in applications such as organ retraction and manipulation during surgery
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