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基于主动状态调整的四足机器人稳定性控制

Stability Control of Quadruped Robot Based on Active State Adjustment.

作者信息

Gu Sai, Meng Fei, Liu Botao, Zhang Zhihao, Sun Nengxiang, Wang Maosen

机构信息

Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.

Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing 100081, China.

出版信息

Biomimetics (Basel). 2023 Mar 9;8(1):112. doi: 10.3390/biomimetics8010112.

Abstract

The quadruped robot has a strong motion performance and broad application prospects in practical applications. However, during the movement of the quadruped robot, it is easy to be affected by external disturbance and environmental changes, which makes it unable to achieve the ideal effect movement. Therefore, it is very important for the quadruped robot to adjust actively according to its own state detection. This paper proposes an active state adjustment control method based on its own state, which can realize disturbance recovery and active environment adaptation. Firstly, the controller is designed according to the physical model of the quadruped robot, and the foot forces are optimized using the quadratic program (QP) method. Then, the disturbance compensation method based on dynamic analysis is studied and combined with the controller itself. At the same time, according to the law of biological movement, the movement process of the quadruped robot is actively adjusted according to the different movement environment, so that it can adapt to various complex environments. Finally, it is verified in a simulation environment and quadruped robot prototype. The results show that the quadruped robot has a strong active disturbance recovery ability and active environment adaptability.

摘要

四足机器人在实际应用中具有强大的运动性能和广阔的应用前景。然而,在四足机器人运动过程中,容易受到外部干扰和环境变化的影响,导致其无法实现理想的运动效果。因此,四足机器人根据自身状态检测进行主动调整非常重要。本文提出了一种基于自身状态的主动状态调整控制方法,该方法可以实现干扰恢复和主动环境适应。首先,根据四足机器人的物理模型设计控制器,并使用二次规划(QP)方法优化足部力。然后,研究基于动态分析的干扰补偿方法并将其与控制器本身相结合。同时,根据生物运动规律,根据不同的运动环境对四足机器人的运动过程进行主动调整,使其能够适应各种复杂环境。最后,在仿真环境和四足机器人原型上进行了验证。结果表明,该四足机器人具有强大的主动干扰恢复能力和主动环境适应能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f941/10046595/985a87887835/biomimetics-08-00112-g001.jpg

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