Date of Award


Document Type

Open Access

Degree Name

Bachelor of Science


Computer Science

First Advisor

John Rieffel




soft robotics, algorithm, genetic algorithm, computation


The field of soft robotics is very promising; applications in-clude urban search and rescue and covert surveillance, but these projects are not yet realized, partly because of the difficulties in soft robot shape and locomotion design. Be-cause of this, traditional design methods do not prove to be effective. This project attempts to come up with solu-tions to this soft robot design problem; utilizing a genetic algorithm, a computer simulation of Darwin’s “Survival of the Fittest,” this project attempts to make soft bodies move. This genetic algorithm evaluates each solution in simulation, and assigns each one a fitness based on distance travelled. Furthermore, this project implements a technique called co-evolution, which evolves two different things in lockstep, uti-lizing new found advancements in one to help bolster the other. This project evolves soft bodies’ physical properties, values that affect how they move, alongside locomotion tech-niques, the gaits defining their movement. Optimizations to this process are realized in the use of scalable soft meshes; this system starts on a simple mesh, and slowly increases its density, reducing the overall computation time.

Included in

Robotics Commons