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Autonomous Navigation Using Multimodal Potential Field to Initiate Interaction with Multiple People

机译:使用多峰势场进行多人交互的自主导航

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In a human-robot interaction, a robot needs to move to a position where the robot can obtain high reliability data of people, such as positions, postures, and voice. This is because the human recognition reliability depends on the positional relation between the people and the robot. In addition, the robot should choose the sensor data which is necessary to perform the interaction task. Therefore, it is necessary to navigate the robot to the position to obtain the data for initiation of the interaction task. Accordingly, we need to design a path-planning method considering sensor characteristics, human recognition reliability, and task contents. Although previous studies proposed path-planning methods using an interaction potential considering sensor characteristics, they did not consider the task contents and the human recognition reliability, which are important for practical application and did not applied to interaction with multiple people. Consequently, we present a path-planning method considering the task contents and the human recognition reliability using multimodal potential field integrating these information. We verified effectiveness of the path-planning method for interaction with multiple people.
机译:在人机交互中,机器人需要移动到可以获取人员的高可靠性数据(例如位置,姿势和语音)的位置。这是因为人的识别可靠性取决于人与机器人之间的位置关系。此外,机器人应选择执行交互任务所需的传感器数据。因此,有必要将机器人导航到该位置以获得用于启动交互任务的数据。因此,我们需要设计一种考虑传感器特性,人类识别可靠性和任务内容的路径规划方法。尽管先前的研究提出了一种考虑到传感器特性的使用交互电位的路径规划方法,但他们并未考虑任务内容和人类识别可靠性,这对于实际应用很重要,并且不适用于与多人交互。因此,我们提出了一种路径计划方法,其中考虑了任务内容和使用集成了这些信息的多峰势场的人类识别可靠性。我们验证了与多人互动的路径规划方法的有效性。

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