TY - GEN
T1 - Autonomous Navigation Using Multimodal Potential Field to Initiate Interaction with Multiple People
AU - Kawasaki, Yosuke
AU - Yorozu, Ayanori
AU - Takahashi, Masaki
PY - 2018/12/27
Y1 - 2018/12/27
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85062990052&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062990052&partnerID=8YFLogxK
U2 - 10.1109/IROS.2018.8594289
DO - 10.1109/IROS.2018.8594289
M3 - Conference contribution
AN - SCOPUS:85062990052
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 7654
EP - 7659
BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Y2 - 1 October 2018 through 5 October 2018
ER -