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Human-robot Interaction Oriented Human-in-the-loop Real-time Motion Imitation on a Humanoid Tri-Co Robot

机译:基于人形Tri-Co机器人的面向人机交互的人在环实时运动模仿

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Inspired by the concept of Tri-Co Robots, a real-time motion imitation based human-robot interaction method is proposed to telemanipulate a life-size humanoid robot. First, a motion capture system is established to retarget the accurate motion data to a skeletal model. Second, the real-time data transfer for a human-in-the-loop control system is realized through the publish-subscribe messaging mechanism in ROS (Robot Operating System). Third, a fast mapping algorithm is developed to convert BVH (BioVision Hierarchy) data into corresponding joint angles which are then encapsulated in a designed communication protocol and sent to a low-level slave controller through a serial port. Finally, visualization terminals render it more convenient to make comparisons between two different but simultaneous motion systems. Experimentation on complicated gesture imitation shows the feasibility of the proposed methodology, and the synchronous latency of less than 0.5 seconds validated its real-time performance. The proposed human-in-the-loop imitation control method enhances robot interaction capability in a more natural way and improves robot adaptability to uncertain and dynamic environments.
机译:受Tri-Co机器人概念的启发,提出了一种基于实时运动模仿的人机交互方法,以远程操纵真人大小的人形机器人。首先,建立运动捕捉系统以将准确的运动数据重新定向到骨骼模型。其次,通过ROS(机器人操作系统)中的发布-订阅消息传递机制来实现人在环控制系统的实时数据传输。第三,开发了一种快速映射算法,可将BVH(BioVision层次结构)数据转换为相应的关节角度,然后将其封装在设计的通信协议中,并通过串行端口发送给低级从属控制器。最后,可视化终端使在两个不同但同时存在的运动系统之间进行比较更加方便。对复杂手势模仿的实验表明了该方法的可行性,而小于0.5秒的同步等待时间验证了其实时性能。所提出的在环仿真控制方法以更自然的方式增强了机器人的交互能力,并提高了机器人对不确定和动态环境的适应性。

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