让四足机器人在低重力下跳跃时自动稳住身体姿态
Modeling and In-flight Torso Attitude Stabilization of a Jumping Quadruped
- 用凸分解生成高效碰撞模型，分层控制躯干姿态与腿部动作
- 仿真中实现横滚/俯仰/偏航90度旋转，分别稳定在6.3/2.4/5.5秒
- 适合研究跳跃机器人、空间行走系统或模型预测控制的开发者
本文研究低重力环境下跳跃四足机器人的建模与姿态控制问题。首先提出一种凸分解方法，用于生成高精度且低成本的碰撞几何模型，以支持敏捷运动。采用分层控制架构，将躯干姿态跟踪与无碰撞腿部动作生成分离处理。两层控制器均使用非线性模型预测控制（NMPC）。为计算所需腿部运动，利用系统对称性设计力矩分配策略，避免自碰撞并简化NMPC求解。通过基于有限状态机的权重切换策略实现实时周期轨迹规划。所提控制器在仿真中成功稳定了横滚、俯仰和偏航方向90度的旋转，分别耗时6.3秒、2.4秒和5.5秒。实验进一步验证了控制器在恒定及变化姿态参考下的稳定性。整体工作为跳跃腿式系统的先进模型驱动姿态控制器开发提供了框架。
原文摘要 · Abstract (English)
This paper addresses the modeling and attitude control of jumping quadrupeds in low-gravity environments. First, a convex decomposition procedure is presented to generate high-accuracy and low-cost collision geometries for quadrupeds performing agile maneuvers. A hierarchical control architecture is then investigated, separating torso orientation tracking from the generation of suitable, collision-free, corresponding leg motions. Nonlinear Model Predictive Controllers (NMPCs) are utilized in both layers of the controller. To compute the necessary leg motions, a torque allocation strategy is employed that leverages the symmetries of the system to avoid self-collisions and simplify the respective NMPC. To plan periodic trajectories online, a Finite State Machine (FSM)-based weight switching strategy is also used. The proposed controller is first evaluated in simulation, where 90 degree rotations in roll, pitch, and yaw are stabilized in 6.3, 2.4, and 5.5 seconds, respectively. The performance of the controller is further experimentally demonstrated by stabilizing constant and changing orientation references. Overall, this work provides a framework for the development of advanced model-based attitude controllers for jumping legged systems.
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