机器人关节故障时，用非抓握方式仍能完成操作，成功率超88%
Exploring How Non-Prehensile Manipulation Expands Capability in Robots Experiencing Multi-Joint Failure
- 通过建模故障约束空间，生成非抓握动作的运动规划图
- 在多关节锁定情况下，可达区域扩大79%
- 无需末端执行器也能完成任务，适合高可靠性场景
本文研究非抓握操作（NPM）与全身交互策略，使机器人在发生双关节及以上锁死故障（LMJ）时仍可执行操作任务。此类故障会限制机器人的构型与控制空间，削弱仅依赖抓握方法的能力。该方法包含三部分：一、建模故障约束下的工作空间；二、生成该空间内非抓握动作的运动学动力学地图；三、采用模拟闭环方法从地图中选取最优操作动作。实验表明，本方法在多关节锁死情况下使可达区域增加79%；当末端执行器失效时，实际操作成功率达88.9%；若末端可用，则成功率达100%。
原文摘要 · Abstract (English)
This work explores non-prehensile manipulation (NPM) and whole-body interaction as strategies for enabling robotic manipulators to conduct manipulation tasks despite experiencing locked multi-joint (LMJ) failures. LMJs are critical system faults where two or more joints become inoperable; they impose constraints on the robot's configuration and control spaces, consequently limiting the capability and reach of a prehensile-only approach. This approach involves three components: i) modeling the failure-constrained workspace of the robot, ii) generating a kinodynamic map of NPM actions within this workspace, and iii) a manipulation action planner that uses a sim-in-the-loop approach to select the best actions to take from the kinodynamic map. The experimental evaluation shows that our approach can increase the failure-constrained reachable area in LMJ cases by 79%. Further, it demonstrates the ability to complete real-world manipulation with up to 88.9% success when the end-effector is unusable and up to 100% success when it is usable.
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