Abstract | ||
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Geckos are highly adaptable creatures, able to scale a variety of slopes, including walls, and can change their gait depending on their environment. Roboticists have tried to implement this behaviour in gecko robots. So far, an open-loop controlled robot without a tail that uses only one specific gait can climb to a 50° slope. In this paper, we propose neural control that allows a gecko robot to climb to a 70° slope by generating different gaits for various slope angles. The control consists of three main components: a central pattern generator (CPG) for generating various rhythmic patterns, CPG post-processing for shaping the CPG signals, and a delay line for transmitting the shaped CPG signals to drive the legs of the gecko robot. The robot uses a body inclination sensor to provide sensory feedback for gait adaptation. When the incline is below 35°, the robot walks with a predefined fast trot gait. If the incline is increased, it will change its gait from the trot gait to an intermediate gait, followed by a slow wave gait, which is both the most stable and the slowest gait, for climbing the steepest slopes. Using this walking strategy, the robot can efficiently climb a variety of slopes using different gaits and can automatically adapt its gait to maximise speed while ensuring stability. |
Year | DOI | Venue |
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2019 | 10.1109/ICAR46387.2019.8981580 | 2019 19th International Conference on Advanced Robotics (ICAR) |
Keywords | Field | DocType |
gecko robot,open-loop controlled robot,neural control,slope angles,central pattern generator,shaped CPG signals,gait adaptation,predefined fast trot gait,intermediate gait,slow wave gait,gait generation,geckos | Astronomy,Creatures,Computer vision,Gecko,Neural control,Gait,Artificial intelligence,Robot,Central pattern generator,Climbing,Climb,Physics | Conference |
ISBN | Citations | PageRank |
978-1-7281-2468-1 | 0 | 0.34 |
References | Authors | |
1 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Arthicha Srisuchinnawong | 1 | 0 | 0.34 |
Donghao Shao | 2 | 0 | 0.68 |
Potiwat Ngamkajornwiwat | 3 | 3 | 2.36 |
Pitiwut Teerakittikul | 4 | 0 | 1.01 |
ZhenDong Dai | 5 | 1 | 2.75 |
Aihong Ji | 6 | 0 | 2.03 |
Poramate Manoonpong | 7 | 226 | 31.35 |