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

Yosuke Kawasaki, Ayanori Yorozu, Masaki Takahashi

Year
2018
Citations
3

Abstract

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.

Keywords

Task (project management)Reliability (semiconductor)Computer scienceRobotMotion planningHuman–robot interactionHuman–computer interactionArtificial intelligenceField (mathematics)Task analysis

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