四足机器人在坍塌地形上安全运动时的承重评估
Load-bearing Assessment for Safe Locomotion of Quadruped Robots on Collapsing Terrain
AI总结：
针对四足机器人在坍塌地形上的安全运动，本文提出融合地形探测、承重分析、MPC控制与状态机的框架，利用关节测量评估稳定性，实验验证其穿越能力。
摘要：
坍塌地形常见于搜救任务或行星探测中，对四足机器人构成重大挑战。本文提出了一种鲁棒的运动框架，通过整合地形探测、承重分析、运动规划和控制策略，实现不稳定表面上的安全导航。与依赖专用传感器或仅依赖外部地形测绘的传统方法不同，我们的方法利用关节测量来评估地形稳定性，无需硬件修改。模型预测控制（MPC）系统优化机器人运动，平衡稳定性和探测约束，而状态机协调地形探测动作，使机器人能够检测可坍塌区域并动态调整其落脚点。在定制坍塌平台和岩石地形上的实验结果表明，该框架能够在保持稳定性并优先考虑安全性的同时穿越坍塌地形。
英文摘要：
Collapsing terrains, often present in search and rescue missions or planetary exploration, pose significant challenges for quadruped robots. This paper introduces a robust locomotion framework for safe navigation over unstable surfaces by integrating terrain probing, load-bearing analysis, motion planning, and control strategies. Unlike traditional methods that rely on specialized sensors or external terrain mapping alone, our approach leverages joint measurements to assess terrain stability without hardware modifications. A Model Predictive Control (MPC) system optimizes robot motion, balancing stability and probing constraints, while a state machine coordinates terrain probing actions, enabling the robot to detect collapsible regions and dynamically adjust its footholds. Experimental results on custom-made collapsing platforms and rocky terrains demonstrate the framework's ability to traverse collapsing terrain while maintaining stability and prioritizing safety.
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