面向四足漫游车的自适应运动策略：量化行星斜坡上何时滑行或行走
Towards An Adaptive Locomotion Strategy For Quadruped Rovers: Quantifying When To Slide Or Walk On Planetary Slopes
AI总结：
针对行星松散倾斜地形上传统足式漫游车运动能效低、有风险的问题，研究对比四足机器人行走与躯干滑行的运输成本，结合仿真与颗粒验证确定策略切换阈值，为行星漫游车自适应运动策略奠定基础。
摘要：
与轮式平台相比，足式漫游车具备更强的机动性，能够在陡峭且不规则的行星地形中导航。然而，在陨石坑壁、洞穴斜坡等松散倾斜表面上，传统的足式运动可能能量效率低下，且对漫游车存在潜在危险。本文开展了一项初步研究，对比了四足机器人在不同坡度、摩擦条件和速度水平下，行走运动与基于躯干的滑行运动的运输成本（Cost of Transport, CoT）。通过识别行走与滑行的CoT曲线交点，我们旨在确定可触发两种策略切换的阈值条件。该方法结合了Isaac Sim中的基于物理的仿真，以及ANSYS-Rocky中的颗粒相互作用验证。我们的研究结果是迈向行星足式漫游车自适应运动策略的初步一步。
英文摘要：
Legged rovers provide enhanced mobility compared to wheeled platforms, enabling navigation on steep and irregular planetary terrains. However, traditional legged locomotion might be energetically inefficient and potentially dangerous to the rover on loose and inclined surfaces, such as crater walls and cave slopes. This paper introduces a preliminary study that compares the Cost of Transport (CoT) of walking and torso-based sliding locomotion for quadruped robots across different slopes, friction conditions and speed levels. By identifying intersections between walking and sliding CoT curves, we aim to define threshold conditions that may trigger transitions between the two strategies. The methodology combines physics-based simulations in Isaac Sim with particle interaction validation in ANSYS-Rocky. Our results represent an initial step towards adaptive locomotion strategies for planetary legged rovers.
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。
