Humanoid robot locomotion system with balancing feedback using leg and arm strategy and stepping strategy

M. Luqman, W. Adiprawita, K. Mutijarsa
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引用次数: 1

Abstract

Humanoid robot must has an ability to move with dynamic motion. Robot is required to walk even get any interference of other robots or other disturbance, and keep its balance. In general, robot motion system is built by 2 kinematics systems, inverse kinematics and forward kinematics. Inverse kinematics is more often used for robot motion because it is more dynamic compare to forward kinematics. Robot motion also has to have a balancing system. In this capstone design, feedback system for robot motion balancing is developed using 2 strategy, leg and arm strategy, and stepping strategy. Leg and arm strategy is a technique to obtain balancing by giving direct feedback to actuator based on Robot Center of Mass (CoM). Stepping is a technique to maintain balance when robot is walking. Stepping is done by making robot motion trajectory to make one of robot's legs take a charge as robot support. Robot motion balancing algorithm has been implemented in robot platform Baldhart v1.0. Robot has ability to keep its balance with maximum disturbance 25° in 4 directions. Robot has ability to move in a plane with different height for maximum 0.6 cm.
基于腿、臂策略和步进策略的仿人机器人平衡反馈运动系统
人形机器人必须具有动态运动的能力。要求机器人在行走时即使受到其他机器人的干扰或其他干扰,也能保持自身的平衡。一般来说,机器人运动系统由逆运动学和正运动学两个运动学系统组成。逆运动学更常用于机器人运动,因为它比正运动学更动态。机器人的运动也必须有一个平衡系统。在本次顶点设计中,采用2策略、腿臂策略和步进策略开发了机器人运动平衡反馈系统。腿臂策略是一种基于机器人质心直接反馈致动器实现平衡的技术。步进是机器人行走时保持平衡的一种技术。步进是通过制作机器人的运动轨迹,使机器人的一条腿担负起支撑机器人的作用。机器人运动平衡算法在机器人平台Baldhart v1.0中实现。机器人具有在4个方向最大扰动25°时保持平衡的能力。机器人能够在不同高度的平面上移动,最大移动距离为0.6厘米。
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