Abstract
This paper proposes a novel algorithm for humanoid robots to walk on unknown uneven terrain by using the Modifiable Walking Pattern Generator (MWPG). The proposed algorithm runs with a finite state machine including ascending and descending states. If the landing time of a swinging leg on unknown uneven terrain is shorter than the assigned single support time, the state is switched to the ascending state. If longer, the state is switched to the descending state. When a swinging leg lands on a surface of unknown uneven terrain, robot receives an impulsive contact force. The average impulsive contact force is reduced by expanding the duration of the contact time with respect to the impulse-momentum equation. According to the change of the step length due to unknown uneven terrain, the newly calculated center of mass (CoM) trajectory in the double support phase after landing the swinging leg is used. The proposed algorithm is used with the modified foot trajectory for adapting to the height of the uneven terrain. The effectiveness of the proposed algorithm is demonstrated through computer simulations using the simulation model of the small-sized humanoid robot, HanSaRam-IX (HSR-IX).
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Kim, YM., Kim, JH. (2015). Modifiable Walking Pattern Generator on Unknown Uneven Terrain. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_11
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DOI: https://doi.org/10.1007/978-3-319-16841-8_11
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16840-1
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