Abstract
The theoretical capability of modular robots to recover their original configuration or function after disintegration caused by external impacts has been cited as an advantage for planetary exploration. The key to achieving self-recovery lies in addressing the stochasticity of disintegration. Here, a self-recovery strategy is proposed for modular planetary exploration robots. Firstly, the recovery process is analyzed to construct a strategy framework and provide the problem definitions and strategy assumptions. Secondly, by standardizing the selection criteria for meta-modules under the stochasticity of disintegration, non-mobile modules can acquire mobility through the meta-module method, thereby laying the groundwork for executable self-recovery. Finally, a comprehensive optimization model is proposed, which encompasses the module interactions arising from stochastic disintegration. By integrating self-recovery characteristics with the simulated annealing algorithm, a solution method is designed to obtain self-recovery plans. Extensive hardware experiments were conducted, and the results demonstrate that the self-recovery strategy operates stably and executes successfully across various configurations and scenarios, thereby validating the feasibility and reliability. In this way, the self-recovery strategy and experiments could substantially advance the application of modular robots in space exploration, while also providing insights for other areas, such as assembly planning and applications involving non-mobile modular robots.
| Original language | English |
|---|---|
| Pages (from-to) | 1188-1200 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Automation Science and Engineering |
| Volume | 23 |
| DOIs | |
| State | Published - 2026 |
Keywords
- Modular robots
- meta-modules
- planetary exploration
- self-reassembly
- self-recovery
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