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JRM Vol.24 No.1 pp. 71-85
doi: 10.20965/jrm.2012.p0071
(2012)

Paper:

Omni-Directional Gait of Multi-Legged Robot on Rough Terrain by Following the Virtual Plane

Kenji Kamikawa*, Tomohito Takubo**, Yasushi Mae**,
Kenji Inoue***, and Tatsuo Arai**

*Hitachizosen Corporation, 2-2-11 Funamachi, Taisho-ku, Osaka 551-0022, Japan

**Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan

***Yamagata University, 4-3-16 Jonan, Yonezawa, Yamagata 992-8510, Japan

Received:
March 9, 2011
Accepted:
July 20, 2011
Published:
February 20, 2012
Keywords:
virtual plane, rough terrain, slope, omnidirectional gait, multi-legged robot
Abstract
This paper proposes a simple gait algorithm for multilegged robots on slopes or rough terrain. This algorithm enables a robot follow a virtual plane defined by grounding points of the legs. The robot does not recognize the surrounding rough terrain. This proposed algorithm has been applied to an actual robot and proven. The robot has a touch sensor on the tip of each leg. The sensors detect contact with the ground, allowing the leg to be planted stably. When the robot moves over rough terrain, the robot body inclines as if becoming parallel to the virtual plane that is defined by the support points of the legs. The ASTERISK robot to which the algorithm has been applied has six limbs that radiate out in six directions, giving it rotational symmetry. Each leg of the robot has a cylindrical working space; the robot can move omnidirectionally without changing its posture. The movement algorithm is an easy, single-pattern operation that maintains a stable state at all times, and the robot can move without high-speed, real-time processing. The operation and effectiveness of this algorithm are verified on a slope and on steps through the experiment.
Cite this article as:
K. Kamikawa, T. Takubo, Y. Mae, K. Inoue, and T. Arai, “Omni-Directional Gait of Multi-Legged Robot on Rough Terrain by Following the Virtual Plane,” J. Robot. Mechatron., Vol.24 No.1, pp. 71-85, 2012.
Data files:
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Last updated on Apr. 22, 2024