Human-Inspired Foot-Spine Coordination Control for Stable Landing of Jumping Robots
Rui Chen, Hao Yang, Bai Li, Lifu Liu, Zean Yuan, Huijiang Wang, Lunfei Liang, Pei Jiang, Jun Luo
- Year
- 2025
- Citations
- 1
- Access
- Open access
Abstract
Abstract Jumping robots are highly capable of overcoming obstacles. However, their explosive force, short duration, and variable trajectories pose significant challenges in achieving stable landings in complex environments. Traditional approaches rely heavily on sophisticated algorithms and electronic sensor feedback systems to ensure landing stability, which increases the implementation complexity. Inspired by the process by which humans complete jumps and achieve stable landings in complex environments, this study proposes a novel landing control method for jumping robots. By designing a mechanically coupled perception-control structure based on mechanical logic computing, the robot simulates the real-time transmission of neural signals triggered by the ground reaction force (GRF) in human reflex loops, thereby simplifying traditional control approaches. Through the collaboration of a flexible mechanical spine and a bistable foot module, the robot achieves an average height of 16.8 cm and a distance of 25.36 cm in consecutive stable jumps. It also demonstrates reliable landing performance on challenging terrain including slopes and cobblestone surfaces. This paper proposes a novel landing control method for jumping robots that simplifies traditional control approaches. The method enables stable landings on complex terrain through a mechanically coupled perception-control structure. This approach has potential applications in tasks requiring mobility over uneven terrain, such as search and rescue.
Keywords
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