TY - GEN
T1 - Closed-loop push recovery for an inexpensive humanoid robot
AU - Hosseinmemar, Amirhossein
AU - Baltes, Jacky
AU - Anderson, John
AU - Lau, Meng Cheng
AU - Lun, Chi Fung
AU - Wang, Ziang
N1 - Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.
PY - 2018
Y1 - 2018
N2 - Active balancing in autonomous humanoid robots is a challenging task due to the complexity of combining a walking gait with dynamic balancing, vision and high-level behaviors. Humans not only walk successfully over even and uneven terrain, but can recover from the interaction of external forces such as impacts with obstacles and active pushes. While push recovery has been demonstrated successfully in expensive robots, it is more challenging with robots that are inexpensive, with limited power in actuators and less accurate sensing. This work describes a closed-loop control method that uses an accelerometer and gyroscope to allow an inexpensive humanoid robot to actively balance while walking and recover from pushes. An experiment is performed to test three hand-tuned closed-loop control configurations; using only a the gyroscope, only the accelerometer, and a combination of both sensors to recover from pushes. Experimental results show that the combination of gyroscope and accelerometer outperforms the other methods with 100% recovery from a light push and 70% recovery from a strong push.
AB - Active balancing in autonomous humanoid robots is a challenging task due to the complexity of combining a walking gait with dynamic balancing, vision and high-level behaviors. Humans not only walk successfully over even and uneven terrain, but can recover from the interaction of external forces such as impacts with obstacles and active pushes. While push recovery has been demonstrated successfully in expensive robots, it is more challenging with robots that are inexpensive, with limited power in actuators and less accurate sensing. This work describes a closed-loop control method that uses an accelerometer and gyroscope to allow an inexpensive humanoid robot to actively balance while walking and recover from pushes. An experiment is performed to test three hand-tuned closed-loop control configurations; using only a the gyroscope, only the accelerometer, and a combination of both sensors to recover from pushes. Experimental results show that the combination of gyroscope and accelerometer outperforms the other methods with 100% recovery from a light push and 70% recovery from a strong push.
KW - Autonomous active balancing
KW - Centroidal moment pivot
KW - Humanoid robot
KW - Push recovery
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U2 - 10.1007/978-3-319-92058-0_22
DO - 10.1007/978-3-319-92058-0_22
M3 - Conference contribution
AN - SCOPUS:85049015530
SN - 9783319920573
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 233
EP - 244
BT - Recent Trends and Future Technology in Applied Intelligence - 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Proceedings
A2 - Ait Mohamed, Otmane
A2 - Mouhoub, Malek
A2 - Sadaoui, Samira
A2 - Ali, Moonis
PB - Springer Verlag
T2 - 31st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems IEA/AIE 2018
Y2 - 25 June 2018 through 28 June 2018
ER -