Evolving legged robots using biologically inspired optimization strategies

When designing a legged robot a small change in one variable can have a significant effect on a number of the robot's characteristics, meaning that making tradeoffs can be difficult. The algorithm presented in this paper uses biologically inspired optimization techniques to identify the effects of changing various robot design variables and determine if there are any general rules which can be applied to the design of a legged robot. Designs produced by this simulation are also compared to existing robot designs and biological systems, showing that the algorithm produces results which require less power and torque than similar robots, and which share a number of characteristics with biological systems.