Bio-inspired Multi-Model Fusion Control for CPG-based Quadrupedal Locomotion
收藏资源简介：
To promote the deployment of quadrupedal robots, this study proposes a novel bio-inspired control scheme. Specifically, inspired by the differentiated modalities of the animal's proximal and distal joints, a multi-model fusion scheme is constructed. First, the hip movement in joint space is obtained by a central pattern generator(CPG), whereby motion gaits, including trotting and galloping, are generated by a coupling network. Then, to generate the knee motion, a CPG-driven finite state machine is first proposed to determine the gait state. On top of this, the spring-loaded inverted pendulum model is utilized to regulate the knee joint's torque command. Furthermore, to enhance stability, online feedback regulation is incorporated to regulate CPG behavior. And, a virtual model control strategy is designed to modify the torque profile of the knee torque. To verify the proposed methodology, hardware experiments are conducted on a newly developed quadrupedal robot. Results demonstrate that \textit{i)} the small-sized robot can reach 0.8 m/s, with high tracking performance; \textit{ii)} compared with the traditional case where CPG generates both hip and knee trajectory directly, the energy consumption is reduced by 11.2\% with our method; \textit{iii)} the robot can realize smooth gait transition on flat ground and robust walking across uneven terrains.
为推动四足机器人的落地部署，本研究提出了一种全新的仿生控制方案。具体而言，受动物肢体近端与远端关节差异化运动模式的启发，我们构建了多模态融合控制框架。首先，通过中枢模式发生器（Central Pattern Generator，CPG）获取关节空间内的髋关节运动，借助耦合网络生成包括小跑（trotting）和疾驰（galloping）在内的运动步态。随后，为生成膝关节运动，本研究首先提出了一种基于CPG驱动的有限状态机以确定步态状态。在此基础上，我们采用弹簧倒立摆模型对膝关节的力矩指令进行调节。此外，为提升控制系统稳定性，我们引入在线反馈调节机制以优化CPG的运动行为，并设计了虚拟模型控制策略以修正膝关节的力矩曲线。为验证所提方法的有效性，我们在一台全新研发的四足机器人平台上开展了硬件实验。实验结果表明：i）该小型机器人可实现0.8 m/s的运动速度，并具备优异的轨迹跟踪性能；ii）相较于传统直接通过CPG生成髋关节与膝关节轨迹的方案，本方法可将能耗降低11.2%；iii）该机器人可在平坦地面实现平滑的步态切换，并能在非平整地形下实现稳健行走。
