A Soft Crawling Robot That Can Self-Repair Material Removal and Deep Lengthwise Cuts, Actuated by Thin McKibben Muscles
Mengfei Xie, Yunhao Feng, Hiroyuki Nabae, Koichi Suzumori
- Year
- 2024
- Citations
- 2
Abstract
Soft robots are prone to damage when they come into contact with sharp objects, decreasing their functionality. Self-repairing soft robots have great potential to restore their functionality after the damage has been repaired. However, for certain damages wherein it is difficult to reconnect the cut surfaces, the existing self-repairing soft robots often require external intervention to establish contact between the cut surfaces and achieve recovery. Therefore, this study proposes a novel self-repairing soft robot composed of thin McKibben muscles and self-healing materials. Experimental validation and mathematical model analysis have demonstrated that this robot can self-repair the hard-to-reconnect cut surface damages, such as material removal and deep lengthwise cuts, by actuating the thin McKibben muscles in the designed sequence. Furthermore, experimental evidence through bending and crawling confirms that this robot exhibits robust self-repair properties. Moreover, this can be achieved without external intervention and shows potential to be extrapolated to other systems.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991