EMMa：面向履带救援机器人的末端稳定性导向移动操作
EMMa: End-Effector Stability-Oriented Mobile Manipulation for Tracked Rescue Robots
AI总结：
本文提出了一种面向履带救援机器人的移动操作框架，通过协调路径优化模型和紧凑成本/约束表示，提高末端操作的稳定性和任务成功率。
摘要：
履带移动操作在救援任务中需要确保机器人运动的可达性和安全性，同时在多变任务需求下维持稳定的末端操作。然而，现有研究在规划和控制层面忽视了许多末端运动属性。本文提出了一种针对履带移动操作的运动生成框架，通过耦合末端和移动基座状态的协调路径优化模型，设计紧凑的成本/约束表示以减轻非线性影响并降低计算复杂性。此外，开发了一种隔离控制方案，包含前馈补偿和反馈调节，以实现机器人协调路径跟踪。大量模拟和现实世界实验表明，所提框架在关键指标上均优于现有最佳方法，包括任务成功率和末端运动稳定性，验证了其在复杂移动操作任务中的有效性和鲁棒性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
