TY - GEN
T1 - Effects of Walking Style and Symmetry on the Performance of Localization Algorithms for a Biped Humanoid Robot
AU - Shiguematsu, Yukitoshi Minami
AU - Brandao, Martim
AU - Takanishi, Atsuo
N1 - Funding Information:
*This study was conducted as part of the Research Institute for Science and Engineering, Waseda University, and as part of the humanoid project at the Humanoid Robotics Institute, Waseda University. It was also supported in part by the Program for Leading Graduate Schools, the Graduate Program for Embodiment Informatics of the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT, Japan), by SolidWorks Japan K.K and Cybernet Systems Co.,Ltd. M. Brandao is funded by UK Research and Innovation and EPSRC, ORCA research hub (EP/R026173/1).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4/25
Y1 - 2019/4/25
N2 - Motivated by experiments showing that humans' localization performance changes with walking parameters, in this paper we explore the effects of walking gait on biped humanoid localization. We focus on walking style (normal and gallop) and gait symmetry (one side slower), and we assess the performance of visual odometry (VO) and kinematic odometry algorithms for the robot's localization. Changing the walking style from normal to gallop slightly improved the performance of the visual localization, which was related to a reduction in torques on the feet. Changing the gait temporal symmetry worsened the performance of the visual algorithms, which according to an analysis of inertial data, is related to an increase of mechanical vibrations and camera rotations. Both changes of gait style and symmetry decreased the performance of the kinematic localization, caused by the increase of vertical ground reaction forces, to which kinematic odometry is very sensitive. These observations support our claim that gait and footstep planning could be used to improve the performance of localization algorithms in the future.
AB - Motivated by experiments showing that humans' localization performance changes with walking parameters, in this paper we explore the effects of walking gait on biped humanoid localization. We focus on walking style (normal and gallop) and gait symmetry (one side slower), and we assess the performance of visual odometry (VO) and kinematic odometry algorithms for the robot's localization. Changing the walking style from normal to gallop slightly improved the performance of the visual localization, which was related to a reduction in torques on the feet. Changing the gait temporal symmetry worsened the performance of the visual algorithms, which according to an analysis of inertial data, is related to an increase of mechanical vibrations and camera rotations. Both changes of gait style and symmetry decreased the performance of the kinematic localization, caused by the increase of vertical ground reaction forces, to which kinematic odometry is very sensitive. These observations support our claim that gait and footstep planning could be used to improve the performance of localization algorithms in the future.
KW - Ego-motion
KW - Humanoid robot
KW - Kinematic odometry
KW - Localization
KW - Visual odometry
KW - WABIAN-2R
UR - http://www.scopus.com/inward/record.url?scp=85065661504&partnerID=8YFLogxK
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U2 - 10.1109/SII.2019.8700398
DO - 10.1109/SII.2019.8700398
M3 - Conference contribution
AN - SCOPUS:85065661504
T3 - Proceedings of the 2019 IEEE/SICE International Symposium on System Integration, SII 2019
SP - 307
EP - 312
BT - Proceedings of the 2019 IEEE/SICE International Symposium on System Integration, SII 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/SICE International Symposium on System Integration, SII 2019
Y2 - 14 January 2019 through 16 January 2019
ER -