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Method for the posture control of bionic mechanical wheel-legged vehicles in hilly and mountainous areas

International Journal of Agricultural and Biological Engineering 2024年第5期17卷 151-162页

作者： Kaoxin Pan Qing Zhang Zhenyu Wang Sibo Wang Aobo Zhou Yong You Decheng Wang Key Laboratory of Modern Agricultural Intelligent Equipment in South China Ministry of Agriculture and Rural AffairsGuangzhou 510630China College of Engineering China Agricultural UniversityBeijing 100083China

In response to the weaknesses of traditional agricultural equipment chassis with poor environmental adaptability and inferior mobility, a novel unmanned agricultural machinery chassis has been developed that can operate stably and efficiently under various complex terrain conditions. Initially, a new wheel-legged structure was designed by drawing inspiration from the motion principles of grasshopper hind legs and combining them with pneumatic-hydraulic linkage mechanisms. Kinematic analysis was conducted on this wheel-legged configuration by utilizing the D-H parameter method, which revealed that its end effector has a travel range of 0-450 mm in the X-direction, 0-840 mm in the Y-direction, and 0-770 mm in the Z-direction, thereby providing the structural foundation for features such as independent four-wheel steering, adjustable wheel track, automatic vehicle body elevation adjustment, and maintaining a level body posture on different slopes. Subsequently, theoretical analysis and structural parameter calculations were completed to design each subsystem of the unmanned chassis. Further, kinematic analysis of the wheel-legged unmanned chassis was carried out using RecurDyn, which substantiated the feasibility of achieving functions like slope leveling and autonomous obstacle negotiation. An omnidirectional leveling control system was also established, taking into account factors such as pitch angle, roll angle, virtual leg deployment, and center of gravity height. Joint simulations using Adams and Matlab were performed on the wheel-legged unmanned chassis, comparing its leveling performance with that of a PID control system. The results indicated that the maximum absolute value of leveling error was 1.08° for the pitch angle and 1.19° for the roll angle, while the standard deviations were 0.216 47° for the pitch angle and 0.176 22° for the roll angle, demonstrating that the wheel-legged unmanned chassis surpassed the PID control system in leveling performance, thus

关键词： hilly areas bionic machinery wheel-legged vehicle posture control prototype testing

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Development of a Bionic Hexapod Robot for Walking on Unstructured Terrain

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Journal of Bionic Engineering 2014年第2期11卷 176-187页

作者： He Zhang Yubin Liu Jie Zhao Jie Chen Jihong Yan State Key Lab of Robotics and System Harbin Institute of Technology Harbin 150080 P. R. China

This paper reports the design methodology and control strategy in the development of a novel hexapod robot HITCR-II that is suitable for walking on unstructured terrain. First, the entire sensor system is designed to equip the robot with the perception of external environment and its internal states. The structure parameters are optimized for improving the dexterity of the robot. Second, a foot-force distribution model and a compensation model are built to achieve posture control. The two models are capable of effectively improving the stability of hexapod walking on unstructured terrain. Finally, the posture control strategy based on Force Distribution and Compensation （PCFDC） is applied to the HITCR-II hexapod robot. The experimental results show that the robot can effectively restrain the vibration of trunk and keep stable while walking and crossing over the un- structured terrains.

关键词： hexapod robot structure optimization posture control force distribution force compensation

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Anisotropic neuro-mechanical compensation for kinematic variability in multi-joint arm postural control

Anisotropic neuro-mechanical compensation for kinematic vari...

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中国神经科学学会第九届全国学术会议暨第五次会员代表大会

作者： Xin HE,Yu-Fan DU,Xin WANG,Ning LAN~* Laboratory of Neuro-modulation and Modeling,Institute of Rehabilitation Engineering,The Med-X Research Institute, School of Biomedical Engineering,Shanghai Jiao Tong University,Shanghai 200030,China

＜正＞Objective The purpose of this study is to analyze the efficiency of neuro-mechanical compensation for kinematic variability during postural *** dependent noise（SDN） in natural neuromuscular recruitment brought intrinsic instability in posture maintaining ***,random drifting of human arm endpoint was substantially suppressed by neuro-mechanical compensation and reflex regulation in normal subjects,and it may become notable in pathological conditions like Parkinson’s *** the efficiency of neuro-mechanical compensation for kinematic variability may help us find out the control principals our brain adopted in position control,and maybe helpful for rehabilitation treatment planning for patients with motor *** We use a realistic virtual arm（VA） model to address this issue through a computational *** properties at muscle, joint,and hand coordinates were evaluated to obtain an estimation of mechanical *** between muscle stiffness and SDN were simulated with simple patterns of feedfoward activation of *** resultant stiffness and drifting in hand were analyzed by principal components and characterized by elliptic *** （1） The extent of random hand drifting ellipse was inversely modulated by the hand stiffness ellipse.（2） Higher levels of muscle activation caused anisotropic increases of hand stiffness mainly in the major axis direction,consequently leading to anisotropic growth of hand drifting.（3） A U-shaped ratio against total muscular energy consumption between the area of hand endpoint stiffness ellipse and that of hand endpoint drifting ellipse,therefore,suggests thai it may not be efficient to counteract internal neural noise by using high levels of muscle stiffness（activation） in multijoint *** A suitable level of muscle stiffness may be optimal in maintaining a steady arm posture with minimal variation.

关键词： muscle stiffness neural noise kinematic variability multi-joint arm posture control

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