履带车辆的伪运动学轨迹控制与规划
Pseudo-Kinematic Trajectory Control and Planning of Tracked Vehicles
AI总结：
本文提出一个基于三大支柱（仿真与面向控制模型、李雅普诺夫反馈控制器、运动规划方案组合）的履带车辆导航框架，以解决建模复杂性和导航设计难题，并通过仿真与实验验证。
摘要：
履带车辆将其重量连续分布在大面积表面（履带）上。这一显著特征使其成为需要在柔软且不平坦地形上行驶的车辆的首选。然而，从机器人学的角度来看，这种灵活性是有代价的：系统建模的复杂性以及由此导致的设计理论上可靠的导航解决方案的困难。在本文中，我们旨在弥合这一差距，提出一个基于三大支柱的履带车辆导航框架。第一个支柱包含两个模型：一个仿真模型和一个面向控制的模型。仿真模型捕捉由土壤-履带相互作用产生的复杂地面力学动力学，并用于在各种操作条件下开发系统的忠实数字孪生。面向控制的模型是伪运动学的且数学上易处理，使得能够设计高效且理论上稳健的控制方案。第二个支柱是一个基于李雅普诺夫的反馈轨迹控制器，提供可认证的跟踪保证。第三个支柱是一组运动规划解决方案，每个方案提供不同的复杂度-精度权衡。所提出方法的各个组成部分通过广泛的仿真和实验数据进行了验证。
英文摘要：
Tracked vehicles distribute their weight continuously over a large surface area (the tracks). This distinctive feature makes them the preferred choice for vehicles required to traverse soft and uneven terrain. From a robotics perspective, however, this flexibility comes at a cost: the complexity of modelling the system and the resulting difficulty in designing theoretically sound navigation solutions. In this paper, we aim to bridge this gap by proposing a framework for the navigation of tracked vehicles, built upon three key pillars. The first pillar comprises two models: a simulation model and a control-oriented model. The simulation model captures the intricate terramechanics dynamics arising from soil-track interaction and is employed to develop faithful digital twins of the system across a wide range of operating conditions. The control-oriented model is pseudo-kinematic and mathematically tractable, enabling the design of efficient and theoretically robust control schemes. The second pillar is a Lyapunov-based feedback trajectory controller that provides certifiable tracking guarantees. The third pillar is a portfolio of motion planning solutions, each offering different complexity-accuracy trade-offs. The various components of the proposed approach are validated through an extensive set of simulation and experimental data.
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。
