Abstract
Motion coordination is a key factor affecting the stability and efficiency of robots. Such coordination involves the intra-limb coordination between each motion stage of a single leg and the inter-limbs coordination among all legs. The motion behaviors of animals, which have developed over a long period of evolution, offer good prototypes for the motion control of robots. In this paper, the locomotion of a quadruped sprawling animal (i.e., gecko) trotting on a horizontal surface was observed, and the feet trajectories around the hip on the same side were analyzed by statistical analysis and curve fitting. Results showed that feet on stance phase maintain the same speed to satisfy the requirement of inter-limb coordination. In swing phase, feet speed decreases from the moving speed to zero at the beginning and increases from zero to the desired speed in the next step at the end. The feet accomplish the transition from the backmost to the foremost position along a smooth curve that can be fit by a cosine function, which has good kinematic and dynamic characters. A foot trajectory planning method for robots was proposed based on the experiment results, which offered references not only for the foot trajectory planning of robots to realize intra-limb coordination but also for the inter-limbs coordination between stance feet during locomotion. Finally, the motion of a sprawling robot is simulated by using the bio-inspired trajectories to show the performance and benefits of the proposed method.
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Recommended by Associate Editor Kyoungchul Kong
Hongkai Li received his M.S. and Ph.D. from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2006 and 2010, respectively. Currently, he is working for Institute of Bioinspired Structure and Surface Engineering in this university as an Assistant Professor. His research interests include motion control of bionic robots and intelligent robotics.
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Li, H., Shi, A. & Dai, Z. A trajectory planning method for sprawling robot inspired by a trotting animal. J Mech Sci Technol 31, 327–334 (2017). https://doi.org/10.1007/s12206-016-1235-x
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DOI: https://doi.org/10.1007/s12206-016-1235-x