Shape-changing robots face control complexity that limits their capabilities. Here, authors develop a genetic algorithm that optimizes actuator grouping, contraction ratios, and timing. This enables complex shape adaptations with fewer control units, which is validated through simulations and physical prototypes.
- Jianzhe Gu
- Ziwen Ye
- Lining Yao
