4.7 Article

Gait optimization of step climbing for a hexapod robot

Journal

JOURNAL OF FIELD ROBOTICS
Volume 39, Issue 1, Pages 55-68

Publisher

WILEY
DOI: 10.1002/rob.22037

Keywords

claw-shape legs; climbing gait; gait optimization; legged robots; step climbing

Categories

Funding

  1. National Natural Science Foundation of China [51605393]
  2. China Postdoctoral Science Foundation [2018M633398]
  3. State Key Laboratory of Robotics and Systems (HIT) [SKLRS-2020-KF-13]
  4. Sichuan Science and Technology Program [2020YJ0035]

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This paper proposes gait optimization for a hexapod robot to climb steps at different heights, enabling it to climb steps 3.9 times the length of its legs. By adjusting body inclination and using reversed claw-shape legs, the robot can overcome high obstacles and improve climbing height.
RHex-style hexapod robot is a type of legged robot which can perform multiple moving gaits according to different applications, due to its simple structure and strong mobility. However, traversing high obstacles has always been a big challenge for legged robots. In this paper, gait optimization of a hexapod robot is proposed for climbing steps at different heights, which even enables the robot to climb the step 3.9 times of the leg length. First, a previous step-climbing gait is optimized by adjusting body inclination when placing front legs on top of the step, which enables RHex with different sizes to perform the rising stage of the gait. Second, to improve the climbing heights, a novel quasi-static climbing gait is proposed by using the reversed claw-shape legs to reach the higher step. The nondeformable legs are used to raise the center of mass (COM) of the body by lifting the front and rear legs alternately so that the front legs can reach the top of the step, then the front and middle legs are lifted alternately to maneuver COM up onto the step. The simulations and dynamic analysis of climbing steps are utilized to verify the feasibility of the improved gait. Finally, the step-climbing experiments at different heights are performed with the optimized gaits to compare with the existing gaits. The results of simulations and experiments show the superiority of the proposed gaits due to climbing higher steps.

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