Date of Award


Document Type

Open Access

Degree Name

Bachelor of Science


Computer Science

First Advisor

John Rieffel




robot, design, mechanism, development, coding


Creating effective designs for soft robots is extremely difficult due to the large number of different possibilities for shape, material properties, and movement mechanisms. Due to the lack of methods to design soft robots, previous research has used evolutionary algorithms to tackle this problem of overwhelming options. A popular technique is to use generative encodings to create designs using evolutionary algorithms because of their modularity and ability to induce large scale coordinated change. The main drawback of generative encodings is that it is difficult to know where along the ontogenic trajectory resides the phenotype with the highest fitness. The two main approaches for addressing this issue are static and scaled developmental timings. In order to compare the effectiveness of each of these two approaches, I have implemented a framework capable of evolving soft robot designs that utilize vibration as a movement mechanism.