【摘要】 为了更好映射人体动作，同时在减轻机械臂自重的基础上提升负载能力，基于人体上肢的肌肉运动机理与骨骼特性，设计一种七自由度气电混合拮抗式仿生机械手臂，采用气动肌腱和伺服关节电机作为驱动源，利用运动学分析机器人末端执行器的位姿和关节角度，规划卧推动作运动轨迹，蒙特卡罗法仿真工作空间。搭建气动肌腱性能测试平台，对气动肌腱的拉力、收缩率、气压之间的关系进行数据测试，采用多项式回归拟合模型选择算法进行曲面拟合，建立三种型号的气动肌腱数学模型。通过仿生机械臂利用PID控制器对回归模型验证，腕部和肘部稳定响应角度精度≤±1.0°,臂长1.08 m,臂重≤18 kg。结果表明，该方法能够有效拟合气动肌腱的非线性关系，拟合优度高。更多还原

【Abstract】 In order to better map the human body movements, and at the same time, to improve the load capacity on the basis of reducing the self-weight of the robotic arm, based on the muscle movement mechanism and skeletal characteristics of the human upper limb, a seven-degree-of-freedom pneumatic-electrical hybrid antagonistic bionic robotic arm is designed using the pneumatic tendon and the servo joint motors as the drive source, and the kinematics are used to analyze the pose of the robot’s end-effector and the joint angle, and to plan trajectory of the horizontal push motion, the Monte Carlo method is used to simulate the workspace.The performance test platform of pneumatic tendon is built, the relationship between tension, contraction rate and air pressure of pneumatic tendon is tested, and the polynomial regression fitting model selection algorithm is used for surface fitting, establish the mathematical models of three types of pneumatic tendon.The regression model is verified using PID controller by the bionic robotic arm, with wrist and elbow stabilised response angle precision ≤±1.0°,arm length 1.08 m, and arm weight ≤18 kg.The results show that the method can effectively fit the nonlinear relationship of the pneumatic tendon, with a high degree of fitting superiority.更多还原