用简化模型优化蛇形机器人运动，实现在狭窄空间自主爬行。
Reduced-Order Model-Based Gait Generation for Snake Robot Locomotion using NMPC
- 基于降阶模型构建优化框架，自动生成适应环境的步态。
- 仿真与实测均实现窄道通过，验证了方法有效性。
- 适合研究受限空间移动机器人或非完整系统控制的学者。
本文提出一种基于优化的运动规划方法，用于蛇形机器人在受限环境中的运动。通过采用降阶模型，该方法简化了规划过程，使优化器能够自主生成步态，并将机器人的足迹约束在狭小空间内。方法在高保真仿真中进行了验证，仿真准确建模了接触动力学和机器人运动。关键的运动策略被识别，并通过硬件实验进一步展示，包括成功穿越狭窄通道的能力。
原文摘要 · Abstract (English)
This paper presents an optimization-based motion planning methodology for snake robots operating in constrained environments. By using a reduced-order model, the proposed approach simplifies the planning process, enabling the optimizer to autonomously generate gaits while constraining the robot's footprint within tight spaces. The method is validated through high-fidelity simulations that accurately model contact dynamics and the robot's motion. Key locomotion strategies are identified and further demonstrated through hardware experiments, including successful navigation through narrow corridors.
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