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

机译:人体机器人的交互导向人类的LOOM循环实时运动模仿于人形的Tri-Co机器人

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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:通过Tri-Co机器人的概念,提出了一种基于实时运动模拟的人机交互方法,以便为人类机器机器机器人重新管理。首先,建立运动捕获系统以将准确的运动数据重新结合到骨架模型。其次,通过ROS(机器人操作系统)中的发布订阅消息机制来实现用于人机控制系统的实时数据传输。第三,开发了一种快速映射算法以将BVH(BioVision层次结构)数据转换成相应的关节角,然后将其封装在设计的通信协议中并通过串行端口发送到低级从控制器。最后,可视化终端使得在两个不同但同时运动系统之间进行比较更方便。复杂手势模仿的实验表明了所提出的方法的可行性,并且验证了其实时性能的同步延迟。所提出的人型仿制控制方法以更自然的方式增强机器人交互能力,并提高了对不确定和动态环境的机器人适应性。

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