Adaptive Impedance Control of Hexapod Robots Based on Virtual Motoneuron System

doi:10.3969/j.issn.1004-132X.2025.02.014

Abstract

Abstract: A hexapod robot platform was established by emulating the structural configuration of an animal torso. An online adaptive motion controller was introduced, which achieved impedance control parameter online learning by mimicking the compliant joint motions of the human arm. Integrated with the existing virtual motoneuron system, the hexapod robot dynamically adapted walking gaits and sped online to cope with diverse complex terrains. The adaptive motion controller exhibited versatility in accommodating different tasks and unknown robot dynamics, enhancing trajectory tracking stability. Finally, through simulation models and physical testing of the hexapod robots, the results demonstrate the effectiveness of the proposed approach in enhancing the robots adaptability.

Key words: hexapod robot, adaptive control, central pattern generator(CPG), virtual motoneuron network

摘要： 模仿动物躯干的构造，搭建了六足机器人平台；提出了在线的自适应运动控制器，通过模仿人类手臂的顺应性关节运动来实现阻抗控制参数的在线学习。与现有的虚拟运动神经系统结合，使得六足机器人可在线适应行走步态和速度，以应对不同的复杂地形。自适应运动控制器可以适应不同的任务和未知的机器人动力学，使得轨迹跟踪行为更稳定。仿真模型和六足机器人实体测试结果证明，该方法可有效提高机器人的适应性。

关键词: 六足机器人, 自适应控制, 中枢神经系统, 虚拟运动网络

CLC Number:

TP242

LIU Chunchao1, ZHU Yaguang1, 2, ZHOU Yating1, HAN Zhigang1. Adaptive Impedance Control of Hexapod Robots Based on Virtual Motoneuron System[J]. China Mechanical Engineering, 2025, 36(02): 315-324,332.

刘春潮1, 朱雅光1, 2, 周亚婷1, 韩志刚1. 基于虚拟运动神经系统的六足机器人自适应运动控制[J]. 中国机械工程, 2025, 36(02): 315-324,332.

References

［1］WETTERGREEN D. Robotic Walking in Natural Terrain:Gait Planning and Behavior-based Control for Statically-stable Walking Robots［M］. Pittsburgh:Carnegie Mellon University, 1995.
［2］BJELONIC M, HOMBERGER T, KOTTEGE N, et al. Autonomous Navigation of Hexapod Robots with Vision-based Controller Adaptation［C］∥2017 IEEE International Conference on Robotics and Automation(ICRA). Singapore, 2017:5561-5568.
［3］BJELONIC M, KOTTEGE N, HOMBERGER T, et al. Weaver:Hexapod Robot for Autonomous Navigation on Unstructured Terrain［J］. Journal of Field Robotics, 2018, 35(7):1063-1079.
［4］PRGR M, CˇEK P, FAIGL J. Cost of Transport Estimation for Legged Robot Based on Terrain Features Inference from Aerial Scan［C］∥2018 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS). Madrid, 2018:1745-1750.
［5］ZENKER S, AKSOY E E, GOLDSCHMIDT D, et al. Visual Terrain Classification for Selecting Energy Efficient Gaits of a Hexapod Robot［C］∥2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Wollongong, 2013:577-584.
［6］朱雅光, 刘春潮, 张亮. 基于虚拟运动神经网络的六足机器人行为控制［J］. 浙江大学学报(工学版), 2022, 56(6):1107-1118.
ZHU Yaguang, LIU Chunchao, ZHANG Liang. Behavior Control of Hexapod Robot Based on Virtual Motoneuron Network［J］. Journal of Zhejiang University(Engineering Science), 2022, 56(6):1107-1118.
［7］KESPER P, GRINKE E, HESSE F, et al. Obstacle/Gap Detection and Terrain Classification of Walking Robots Based on a 2D Laser Range Finder［C］∥Nature-Inspired Mobile Robotics. Shenzhen, 2013:419-426.
［8］ZHU Yaguang, ZHANG Liang, MANOONPONG P. Virtual Motoneuron Activation for Goal-directed Locomotion of a Hexapod Robot［C］∥2020 5th International Conference on Advanced Robotics and Mechatronics(ICARM). Shenzhen, 2020:380-386.
［9］FOCCHI M, del PRETE A, HAVOUTIS I, et al. High-slope Terrain Locomotion for Torque-controlled Quadruped Robots［J］. Autonomous Robots, 2017, 41(1):259-272.
［10］ZHU Yaguang, JIN Bo, LI Wei. Leg Compliance Control of a Hexapod Robot Based on Improved Adaptive Control in Different Environments［J］. Journal of Central South University, 2015, 22(3):904-913.
［11］XIONG Xiaofeng, WRGTTER F, MANOONPONG P. Adaptive and Energy Efficient Walking in a Hexapod Robot under Neuromechanical Control and Sensorimotor Learning［J］. IEEE Transactions on Cybernetics, 2016, 46(11):2521-2534.
［12］XIONG Xiaofeng, WRGTTER F, MANOONPONG P. Neuromechanical Control for Hexapedal Robot Walking on Challenging Surfaces and Surface Classification［J］. Robotics and Autonomous Systems, 2014, 62(12):1777-1789.
［13］HOMCHANTHANAKUL J, MANOONPONG P. Continuous Online Adaptation of Bioinspired Adaptive Neuroendocrine Control for Autonomous Walking Robots［J］. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(5):1833-1845.
［14］THOR M, MANOONPONG P. Versatile Modular Neural Locomotion Control with Fast Learning［J］. Nature Machine Intelligence, 2022, 4:169-179.
［15］MIRLETZ B T, BHANDAL P, ADAMS R D, et al. Goal-directed CPG-based Control for Tensegrity Spines with Many Degrees of Freedom Traversing Irregular Terrain［J］. Soft Robotics, 2015, 2(4):165-176.
［16］BING Zhenshan, CHENG Long, CHEN Guang, et al. Towards Autonomous Locomotion:CPG-based Control of Smooth 3D Slithering Gait Transition of a Snake-like Robot［J］. Bioinspiration & Biomimetics, 2017, 12(3):035001.
［17］YANG Chenguang, GANESH G, HADDADIN S, et al. Human-like Adaptation of Force and Impedance in Stable and Unstable Interactions［J］. IEEE Transactions on Robotics, 2011, 27(5):918-930.
［18］YANG Chenguang, JIANG Yiming, HE Wei, et al. Adaptive Parameter Estimation and Control Design for Robot Manipulators with Finite-time Convergence［J］. IEEE Transactions on Industrial Electronics, 2018, 65(10):8112-8123.
［19］YANG Chenguang, CHEN Chuize, HE Wei, et al. Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives［J］. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(3):777-787.
［20］XIONG Xiaofeng, MANOONPONG P. Adaptive Motor Control for Human-like Spatial-temporal Adaptation［C］∥2018 IEEE International Conference on Robotics and Biomimetics(ROBIO). Kuala Lumpur, 2018:2107-2112.
［21］XIONG Xiaofeng, MANOONPONG P. Online Sensorimotor Learning and Adaptation for Inverse Dynamics Control［J］. Neural Networks, 2021, 143:525-536.
［22］ZHANG Shuang, DONG Yiting, OUYANG Yuncheng, et al. Adaptive Neural Control for Robotic Manipulators with Output Constraints and Uncertainties［J］. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(11):5554-5564.
［23］朱雅光, 朱建伟, 李茹月, 等. 基于神经-肌肉架构的仿生并联躯干柔顺控制［J］. 中国机械工程, 2022, 33(13):1576-1585.
ZHU Yaguang, ZHU Jianwei, LI Ruyue, et al. Neuromuscular Architecture Based Compliance Control of Bionic Parallel Torsos［J］. China Mechanical Engineering, 2022, 33(13):1576-1585.
［24］ZHU Yaguang, ZHANG Liang, MANOONPONG P. Generic Mechanism for Waveform Regulation and Synchronization of Oscillators:an Application for Robot Behavior Diversity Generation［J］. IEEE Transactions on Cybernetics, 2022, 52(6):4495-4507.
［25］ZHU Yaguang, ZHANG Liang, GUO Wanjin,et al. A Simple and Flexible Movement Control Method for a Hexapod Walking Robot［C］∥Synergy of Automation, IoT & AI. CLAWAR Association Ltd.Kuala Lumpur, 2019:79-86.
［26］ZHU Yaguang, GUO Tong, LIU Qiong, et al. A Study of Arbitrary Gait Pattern Generation for Turning of a Bio-inspired Hexapod Robot［J］. Robotics and Autonomous Systems, 2017, 97:125-135.
［27］ZHU Yaguang, WU Yongsheng, LIU Qiong, et al. A Backward Control Based on σ -Hopf Oscillator with Decoupled Parameters for Smooth Locomotion of Bio-inspired Legged Robot［J］. Robotics and Autonomous Systems, 2018, 106:165-178.
［28］ZHU Yaguang, ZHOU Shuangjie, GAO Dongxiao, et al. Synchronization of Non-linear Oscillators for Neurobiologically Inspired Control on a Bionic Parallel Waist of Legged Robot［J］. Frontiers in Neurorobotics, 2019, 13:59.
［29］GIBSON G, DOSUNMU-OGUNBI O, GONG Yukai, et al. Terrain-Adaptive, ALIP-based Bipedal Locomotion Controller via Model Predictive Control and Virtual Constraints［C］∥2022 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS). Kyoto, 2022:6724-6731.
［30］SUN Yu, UBELLACKER W L, MA W L, et al. Online Learning of Unknown Dynamics for Model-based Controllers in Legged Locomotion［J］. IEEE Robotics and Automation Letters, 2021, 6(4):8442-8449.

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