Robot-to-Human Object Handover using a Behavioural Control Strategy
Robot-to-Human Object Handover using a Behavioural Control Strategy
复制标题
使用行为控制策略的机器人到人类的物体切换
DOI：
10.1109/icsima.2018.8688784
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Paramin Neranon
中科院分区：
文献类型：
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作者：
Paramin Neranon
目前，机器人学的最新研究成果使人类和机器人之间的密切互动成为可能。这项研究的重点是设计和开发一套适当的行为控制策略，用于机器人到人类的对象切换，首先了解如何使用等价的人-人对象切换来建立基于机器人行为的方法的框架。为了实现这一目标，为了了解两个人类参与者之间的触觉交互的动力学和运动学行为特征，进行了一个真实世界的人与人之间的物体转移任务。测量了作为时间函数的给予者和接受者之间的相互作用力的轮廓，并评估了它们在执行协作任务时是如何被调制的。基于所提出的关键特征，这些特征随后可用于设计和开发基于人类行为的服务机器人的概念指南。采用基于位置的比例加积分(PI)和模糊逻辑控制(FLC)算法对机器人末端执行器的位置和作用力进行实时控制。仿真结果比较了PI和FLC控制策略的优劣。结果表明，被控机器人性能的定量测量结果与人类的测量结果接近，可以认为是可以接受的人-机器人交互。有效的物体转移任务使机器人能够安全、可靠、及时地将物体成功地传递给人类。然而，经过对试验结果的仔细分析，基于控制的FLC方案通过对非线性系统的动态进行主动补偿而略优于PI控制，并表现出更好的整体性能和稳定性。
Recent research results in robotics currently make possible the close interaction between humans and robots. This research focuses on the design and development of an appropriate set of behaviour control strategies for robot-to-human object handover by first understanding how an equivalent human-human object handover can be used to establish a framework for a robotic behaviour-based approach. To achieve this goal, a real-world human-to-human object transferring task has been carried out in order to understand the dynamic and kinematic behavioural characteristics of the haptic interaction between two human participants. The profiles of interactive forces between the giver and receiver were measured as a function of time, and how they are modulated while performing the cooperative tasks, was evaluated. Based on key features as proposed, these can be subsequently used to design and develop the conceptual guideline for a human-like behaviour-based service robot. Position-based force control using proportional plus integral (PI) and fuzzy logic control (FLC) algorithms were adopted to control the robot end effector position and interactive force in real-time. The results allowed a comparison of the PI and FLC control strategies. It can be concluded that the quantitative measurement of the controlled robot performance is close to that of the human and can be considered acceptable for human-robot interaction. The effective object transferring tasks provide robot to be able to successfully pass the object to the human in a safe, reliable and timely manner. However, after careful analysis with regard the test results, the control based FLC scheme was shown to be slightly superior to PI control by actively compensating for the dynamics in the non-linear system and demonstrated better overall performance and stability.