Dynamic walking pattern generation for a humanoid robot based on optimal gradient method

Nagasaka, Ken; Inoue, H.; Inaba, Makoto

doi:10.1109/icsmc.1999.816673

Cited by 123 publications

(76 citation statements)

References 8 publications

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“…Many studies on biped walking robots have been performed since 1970 [1][2][3][4]. During that period, biped walking robots have transformed into biped humanoid robots through the technological development.…”

Section: Introductionmentioning

confidence: 99%

Walking Control Algorithm of Biped Humanoid Robot on Uneven and Inclined Floor

Kim

Park

2007

J Intell Robot Syst

195

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This paper describes walking control algorithm for the stable walking of a biped humanoid robot on an uneven and inclined floor. Many walking control techniques have been developed based on the assumption that the walking surface is perfectly flat with no inclination. Accordingly, most biped humanoid robots have performed dynamic walking on well designed flat floors. In reality, however, a typical room floor that appears to be flat has local and global inclinations of about 2 degrees. It is important to note that even slight unevenness of a floor can cause serious instability in biped walking robots. In this paper, the authors propose an online control algorithm that considers local and global inclinations of the floor by which a biped humanoid robot can adapt to the floor conditions. For walking motions, a suitable walking pattern was designed first. Online controllers were then developed and activated in suitable periods during a walking cycle. The walking control algorithm was successfully tested and proved through walking experiments on an uneven and inclined floor using KHR-2 (KAIST Humanoid robot-2), a test robot platform of our biped humanoid robot, HUBO.

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Section: Introductionmentioning

confidence: 99%

Walking Control Algorithm of Biped Humanoid Robot on Uneven and Inclined Floor

Kim

Park

2007

J Intell Robot Syst

195

View full text Add to dashboard Cite

show abstract

“…Finally, learning algorithms for dynamic walking must deal with dynamic discontinuities caused by collisions with the ground and with the problem of delayed reward -torques applied at one time may have an effect on the performance many steps into the future. In area of humanoid robotics, there are several approaches of reinforcement learning (Benbrahim & Franklin, 1997;Chew & Pratt, 2002;Li et al , 1992;Mori et al, 2004;Morinoto et al, 2004;Nagasaka et al, 1999;Nakamura et al, 2003;Salatian et al, 1997;Zhou & Meng, 2000) with additional demands and requirements because high dimensionality of the control problem.…”

Section: Reinforcement Learning Framework and Reinforcement Learning mentioning

confidence: 99%