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

机译:人形机器人机器人系统,使用腿部和臂策略和步进策略进行平衡反馈

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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.
机译:人形机器人必须具有动态运动的能力。机器人需要走路甚至得到其他机器人或其他干扰的任何干扰,并保持平衡。通常,机器人运动系统由2个运动学系统,逆运动学和前向运动学构建。逆运动学更常用于机器人运动,因为它与向前运动学比较更动态。机器人运动也必须具有平衡系统。在此Capstone设计中,使用2策略,腿和臂策略和步进策略开发了机器人运动平衡的反馈系统。腿和ARM策略是一种通过基于机器人的质量(COM)的直接反馈来获得平衡的技术。踩踏是一种在机器人行走时保持平衡的技术。踩踏是通过制作机器人运动轨迹来完成的,使机器人的腿之一充电作为机器人支持。机器人运动平衡算法已在机器人平台BALDHART V1.0中实现。机器人能够在4个方向上保持其余的25°25°的平衡。机器人能够在具有不同高度的平面中移动,最大为0.6厘米。

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