We compare two previous approaches for hopping height control to the new scheme proposed in this paper. This new approach is an example of work in the developing area of neural-mechanical systems and has some very simplified versions of building blocks observed in nature, including a central pattern generator. Explicit formulas for hopping height and conditions for stability were obtained for all three approaches based on approximate Poincare return maps (not included). We also present a novel robot leg design and experimental data which supports our analysis. Our adaptive periodic forcing approach is shown to be comparable or out-perform the other two methods in terms of bandwidth requirement, hopping height, and stability properties.

This paper presents a novel robot leg design. The leg is powered by a DC motor which drives elastic tendons to turn a foot. The tendons store elastic energy just as in nature. Preliminary experimental results show the leg has a well-defined resonance which can be exploited to produce hopping. We also offer a comparison of our leg with the cat hindlimb. Eventually, the leg will be part of a quadrupedal robot.