TY - GEN
T1 - Human-leading navigation for gait measurement robot in living space
AU - Yorozu, Ayanori
AU - Takahashi, Masaki
N1 - Funding Information:
This study was supported by "A Framework PRINTEPS to Develop Practical Artificial Intelligence" of the Core Research for Evolutional Science and Technology (CREST) of the Japan Science and Technology Agency (JST) and JSPS KAKENHI Grant Number 16H04290.
Publisher Copyright:
© 2016 ACM.
PY - 2016/12/7
Y1 - 2016/12/7
N2 - Gait measurements such as several-meters walk tests and trainings are carried out to evaluate walking ability during health promotion and preventive long-term care services. It is necessary to track both legs and measure the walking parameters such as stride length can be used for fall-risk assessment across several meters. We have proposed a gait measurement robot (GMR): moving gait measurement system for a long-distance walk tests and evaluating dual-task performance while keeping a constant distance. The GMR estimates its own pose and the position of both legs of the participant. The GMR leads the participant from the start to the goal of the walk test while maintaining a certain distance from the participant. To lead the participant in the human living space, the GMR has to detect the movable passage and determine the translational motion considering the velocity of the participant and obstacle avoidance. In this study, we propose a sensor-based realtime motion control method for the GMR considering the leading participant toward the movable passage and obstacle avoidance using fuzzy set theory in a long-distance walk test. To verify the effectiveness of the proposed method, we carried out the experiments in a corridor.
AB - Gait measurements such as several-meters walk tests and trainings are carried out to evaluate walking ability during health promotion and preventive long-term care services. It is necessary to track both legs and measure the walking parameters such as stride length can be used for fall-risk assessment across several meters. We have proposed a gait measurement robot (GMR): moving gait measurement system for a long-distance walk tests and evaluating dual-task performance while keeping a constant distance. The GMR estimates its own pose and the position of both legs of the participant. The GMR leads the participant from the start to the goal of the walk test while maintaining a certain distance from the participant. To lead the participant in the human living space, the GMR has to detect the movable passage and determine the translational motion considering the velocity of the participant and obstacle avoidance. In this study, we propose a sensor-based realtime motion control method for the GMR considering the leading participant toward the movable passage and obstacle avoidance using fuzzy set theory in a long-distance walk test. To verify the effectiveness of the proposed method, we carried out the experiments in a corridor.
KW - Autonomous mobile robot
KW - Gait measurement
KW - Navigation
UR - http://www.scopus.com/inward/record.url?scp=85016417417&partnerID=8YFLogxK
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U2 - 10.1145/3029610.3029636
DO - 10.1145/3029610.3029636
M3 - Conference contribution
AN - SCOPUS:85016417417
T3 - ACM International Conference Proceeding Series
SP - 51
EP - 55
BT - Proceedings of the 4th International Conference on Control, Mechatronics and Automation, ICCMA 2016
PB - Association for Computing Machinery
T2 - 4th International Conference on Control, Mechatronics and Automation, ICCMA 2016
Y2 - 7 December 2016 through 11 December 2016
ER -
