Abstract
In the past few decades, people have been trying to address the issue of walking instability in bipedal robots in uncertain environments. However, most control methods currently have still failed to achieve robust walking of bipedal robots under uncertain disturbances. Existing research mostly focuses on motion control methods for robots on uneven terrain and under sudden impact forces, with little consideration for the problem of continuous and intense external force disturbances in uncertain environments. In response to this issue, a disturbance-robust control method based on adaptive feedback compensation is proposed. First, based on the Lagrangian method, the dynamic model of a bipedal robot under different types of external force disturbances was established. Subsequently, through dynamic analysis, it was observed that classical control methods based on hybrid zero dynamics failed to consider the continuous and significant external force disturbances in uncertain environments. Therefore, an adaptive feedback compensation controller was designed, and an adaptive parameter adjustment optimization algorithm was proposed based on walking constraints to achieve stable walking of bipedal robots under different external force disturbances. Finally, in numerical simulation experiments, comparative analysis revealed that using only a controller based on hybrid zero dynamics was insufficient to converge the motion of a planar five-link bipedal robot subjected to periodic forces or bounded noise disturbances to a stable state. In contrast, in the adaptive feedback compensation control method, the use of an adaptive parameter adjustment optimization algorithm to generate time-varying control parameters successfully achieved stable walking of the robot under these disturbances. This indicates the effectiveness of the adaptive parameter adjustment algorithm and the robustness of the adaptive feedback compensation control method.
摘要
在过去的几十年里, 人们一直试图解决双足机器人在不确定环境中行走不稳定的问题. 然而, 目前大多数控制方法仍然无法实 现双足机器人在不确定扰动下的鲁棒行走. 现有研究大多集中于不平坦地形和脉冲力下该类机器人的运动控制方法上, 很少考虑不确 定环境中的连续变化且强度较大的外部力扰动问题. 针对此问题, 提出了一种基于自适应反馈补偿的扰动鲁棒控制方法. 首先, 基于拉 格朗日方法, 建立了双足机器人在不同类型外力扰动下的动力学模型. 随后, 通过动力学分析发现, 基于混合零动力学的经典控制方法 未能考虑不确定环境中连续变化且幅值较大的外力扰动影响. 为此, 设计了一种自适应反馈补偿控制器, 并基于步行约束条件提出了 自适应参数调整优化算法, 以实现在不同外力扰动下双足机器人的稳定行走. 最后, 在数值仿真实验中通过比较分析发现, 仅采用基于 混杂零动态的控制器, 无法使受周期力或有界噪声扰动作用的平面五连杆双足机器人的运动收敛到稳定状态, 而在自适应反馈补偿控 制方法中通过采用自适应参数调整优化算法生成随时间变化的控制参数, 成功实现了机器人在这些扰动作用下的稳定行走, 从而表明 了自适应参数调整算法的有效性和自适应反馈补偿控制方法的鲁棒性.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant No. 12332003), CIE-Tencent Robotics X Rhino-Bird Focused Research Program, and Zhejiang Provincial Natural Science Foundation of China (Grant No. LY23E050010).
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Author contributions Zijing Li: Development of methodology; creation of models; conducting the research and investigation process, specifically performing the data collection; preparation, creation and presentation of the published work, specifically visualization/data presentation; original draft, including preparation and creation of the published work. Jinlin Zhang: Design of methodology; application of mathematical and computational techniques to analyze study data. Mengyue Lu: Development of methodology; application of mathematical and computational techniques to analyze study data. Wanchao Chi: Oversight for the research activity planning; provision of study materials, laboratory samples and computing resources; partially financial support for the project leading to this publication. Chong Zhang: Oversight for the research activity planning; provision of study materials, laboratory samples and computing resources; partially financial support for the project leading to this publication. Shenghao Zhang: Oversight for the research activity planning; provision of study materials, laboratory samples and computing resources; partially financial support for the project leading to this publication. Yuzhen Liu: Oversight for the research activity planning; provision of study materials, laboratory samples and computing resources; partially financial support for the project leading to this publication. Chunbiao Gan: Oversight and leadership responsibility for the research activity planning and execution, including mentorship external to the core team; conceptualization – ideas, formulation and evolution of overarching research goals and aims; review & editing – preparation, creation and presentation of the published work.
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Li, Z., Zhang, J., Lu, M. et al. Adaptive feedback compensation control method for bipedal robot walking under continuous external disturbances. Acta Mech. Sin. 40, 524007 (2024). https://doi.org/10.1007/s10409-024-24007-x
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DOI: https://doi.org/10.1007/s10409-024-24007-x