Sensor feedback modification methods that are suitable for the short cycle pattern generation of humanoid walking

A sensor feedback framework that realizes robust walking of humanoids are discussed in the present paper. We have proposed an online walking control system that generates a dynamically stable motion pattern in short cycles, such as 40 [ms]. The system is capable of reflecting the actual motion status modified by sensor feedback to the pattern generation of the next period so that the long-term stability of the walking is maintained using the dynamic model. We herein propose three categories of adaptation as a framework for realizing robust walking via the short-cycle generation system: 1) absorption of the error of the dynamic model, 2) reactive adaptation to the disturbance, and 3) adjustment of the parameters that are used to generate the walking pattern. Feedback methods for each category are discussed and validated on the full-size humanoid HRP-2.

[1]  Joel E. Chestnutt,et al.  A tiered planning strategy for biped navigation , 2004, 4th IEEE/RAS International Conference on Humanoid Robots, 2004..

[2]  Kazuhito Yokoi,et al.  Biped walking pattern generation by using preview control of zero-moment point , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[3]  Atsuo Takanishi,et al.  Physical interaction between human and a bipedal humanoid robot-realization of human-follow walking , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[4]  K. Hirai,et al.  Current and future perspective of Honda humamoid robot , 1997 .

[5]  Michael Gienger,et al.  Sensor and control design of a dynamically stable biped robot , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[6]  H. Inoue,et al.  Dynamic walking pattern generation for a humanoid robot based on optimal gradient method , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[7]  Masayuki Inaba,et al.  Online generation of humanoid walking motion based on a fast generation method of motion pattern that follows desired ZMP , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Yoshihiko Nakamura,et al.  A Fast Online Gait Planning with Boundary Condition Relaxation for Humanoid Robots , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[9]  Kikuo Fujimura,et al.  The intelligent ASIMO: system overview and integration , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Fumio Kanehiro,et al.  Humanoid robot HRP-2 , 2008, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  Masahiro Fujita,et al.  Real-Time Path Planning for Humanoid Robot Navigation , 2005, IJCAI.

[12]  Atsuo Takanishi,et al.  Development of a Biped Walking Robot Adapting to an Unknown Uneven Surface , 1996 .

[13]  Jun-Ho Oh,et al.  Online free walking trajectory generation for biped humanoid robot KHR-3(HUBO) , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[14]  Shuuji Kajita,et al.  An Analytical Method for Real-Time Gait Planning for Humanoid Robots , 2006, Int. J. Humanoid Robotics.

[15]  Satoshi Kagami,et al.  High frequency walking pattern generation based on preview control of ZMP , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[16]  Masayuki Inaba,et al.  Online mixture and connection of basic motions for humanoid walking control by footprint specification , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[17]  Satoshi Kagami,et al.  High frequency dynamically stable walking pattern generation that enables change of foot placement d , 2006 .

[18]  Shuuji Kajita,et al.  International Journal of Humanoid Robotics c ○ World Scientific Publishing Company An Analytical Method on Real-time Gait Planning for a Humanoid Robot , 2022 .

[19]  Atsuo Takanishi,et al.  Development of a bipedal humanoid robot having antagonistic driven joints and three DOF trunk , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).