优化机器人步态以降低关节负荷，兼顾稳定与移动能力
Gait Generation Balancing Joint Load and Mobility for Legged Modular Robots with Easily Detachable Joints
- 用NSGA-III算法求解多目标最优步态，平衡关节负载与运动性能
- 在斜坡和台阶场景中实现稳定行走，显著降低关节扭矩峰值
- 适合需频繁拆卸关节的模块化足式机器人设计与控制
模块化机器人虽具灵活性，但运动时关节扭矩过大易引发机械故障，尤其在可拆卸关节上风险更高。为此，我们提出基于NSGA-III算法的优化框架，不只追求运动性，而是通过求解帕累托最优解，在降低关节负载的同时保持必要的运动速度与稳定性。仿真与实物实验表明，该方法能有效生成适用于斜坡、台阶等复杂地形的步态，确保结构完整性且不牺牲整体移动能力。
原文摘要 · Abstract (English)
While modular robots offer versatility, excessive joint torque during locomotion poses a significant risk of mechanical failure, especially for detachable joints. To address this, we propose an optimization framework using the NSGA-III algorithm. Unlike conventional approaches that prioritize mobility alone, our method derives Pareto optimal solutions to minimize joint load while maintaining necessary locomotion speed and stability. Simulations and physical experiments demonstrate that our approach successfully generates gait motions for diverse environments, such as slopes and steps, ensuring structural integrity without compromising overall mobility.
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