Optimizing Vertical Jumping Height of Single-Legged Robots with Passive TOE Joints Using the Genetic Algorithm

Abstract

Legged robots have been interesting for researchers because they can move on uneven terrain and operate in dangerous areas for humans. Among these robots, the single-legged robot is an excellent choice to study because they are simpler than another legged robot. In this paper, we have designed a single-legged robot similar to the anatomy of the human leg. It consists of four active joints and one passive joint. The hip, knee, and ankle joint are considered active joints, and the toe joint is a passive joint. To make the simulation more accurate, we should define the physical property of the environment in detail. So, ground contact and friction model should be specified. After defining the robot model, we designed joint motion. Path planning aims to make the robot jump in the vertical direction. Besides, the robot must start jumping on the toe joint. The toe joint stiffness and damping play the leading role in jumping height. So, there should be optimum values for these parameters. The genetic algorithm is then used to optimize jumping height.