提升履带式救援机器人末端执行器在复杂环境下的操作稳定性。
EMMa: End-Effector Stability-Oriented Mobile Manipulation for Tracked Rescue Robots
- 耦合末端与底盘状态的路径优化模型，降低计算复杂度。
- 实测任务成功率与末端稳定性显著优于当前最优方法。
- 适合需要高精度末端控制的救援机器人场景使用。
履带式移动机械臂在救援任务中的自主运行不仅需保障运动可达性与安全性，还需在多样任务需求下维持末端执行器的操作稳定性。然而，现有研究在规划与控制层面均忽视了末端运动的诸多特性。本文提出一种面向末端稳定性的移动操作运动生成框架，构建耦合末端与移动基座状态的协同路径优化模型，并设计紧凑的成本/约束表示以缓解非线性问题、降低计算复杂度。同时，开发了一种包含前馈补偿与反馈调节的独立控制策略，实现机器人协调路径跟踪。在多种模拟与真实救援场景下的实验表明，所提框架在任务成功率和末端运动稳定性等关键指标上持续优于当前最优方法，验证了其在复杂移动操作任务中的有效性与鲁棒性。
原文摘要 · Abstract (English)
The autonomous operation of tracked mobile manipulators in rescue missions requires not only ensuring the reachability and safety of robot motion but also maintaining stable end-effector manipulation under diverse task demands. However, existing studies have overlooked many end-effector motion properties at both the planning and control levels. This paper presents a motion generation framework for tracked mobile manipulators to achieve stable end-effector operation in complex rescue scenarios. The framework formulates a coordinated path optimization model that couples end-effector and mobile base states and designs compact cost/constraint representations to mitigate nonlinearities and reduce computational complexity. Furthermore, an isolated control scheme with feedforward compensation and feedback regulation is developed to enable coordinated path tracking for the robot. Extensive simulated and real-world experiments on rescue scenarios demonstrate that the proposed framework consistently outperforms SOTA methods across key metrics, including task success rate and end-effector motion stability, validating its effectiveness and robustness in complex mobile manipulation tasks.
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