Evolutionary Co-Design of Morphology and Control of Soft Tensegrity Modular Robots with Programmable Stiffness
This work addresses the difficulty in designing and controlling tensegrity robots for robotics applications, but it is incremental as it builds on existing co-evolution methods with a focus on stiffness.
The paper tackled the challenge of designing soft tensegrity modular robots by co-evolving morphology and control, and demonstrated that varying module stiffness leads to different optimal designs and locomotion strategies, with results showing specific performance improvements in simulation.
Tensegrity structures are lightweight, can undergo large deformations, and have outstanding robustness capabilities. These unique properties inspired roboticists to investigate their use. However, the morphological design, control, assembly, and actuation of tensegrity robots are still difficult tasks. Moreover, the stiffness of tensegrity robots is still an underestimated design parameter. In this article, we propose to use easy to assemble, actuated tensegrity modules and body-brain co-evolution to design soft tensegrity modular robots. Moreover, we prove the importance of tensegrity robots stiffness showing how the evolution suggests a different morphology, control, and locomotion strategy according to the modules stiffness.