Ph.D Thesis

Ph.D StudentGaathon Adar
SubjectDevelopment of a Robotic Leg and Minimalistic
Control Methods for Increased the Robustness of a
Running Robot
DepartmentDepartment of Autonomous Systems and Robotics
Supervisor ASSOCIATE PROF. Amir Degani


The superior ability of dynamic legged locomotion to traverse rough terrain relative to the wheeled or tracked mechanisms comes with the cost of fragile stability. As opposed to the commonly used closed loop control schemes, simple control schemes that only use a few basic detection sensors, improve the stability of simple robots when applying a single controller. Controlling the leg angle during descent of our hopping monopod helps it keep its balance when traversing unforeseen rough terrain. Exploiting multiple controllers simultaneously, such as the free leg-length and stiffness, can further improve robustness but is often mechanically hard to implement. To overcome the mechanical complexity of designing and implementing multiple controllers, we investigate a curved leg shape that applies variable leg stiffness and free leg-length coupled with the controller, which is the leg angle during descent.

We develop models that are based on the well-known SLIP (Spring Loaded Inverted Pendulum) model, that manifest the coupling of physical parameters with the leg angle and capture the rolling motion. Our work uses these models to simulate the effect of an optimal combination of parameters during the stance phase of a monopod on the ability to reach a desired relative height above terrain, which corresponds to long-term stability, as was previously demonstrated. We construct measures for robustness to quantify robustness. When traversing unknown rough terrain, such optimal coupling can increase robustness to perturbations in the initial horizontal velocity in 92% relative to the optimized SLIP model with constant parameters.

We further investigate the ability of a single leg shape to modify relative heights, to better accommodate terrain roughness, with only a change in the leg angle controller. We exploit the fact that as various areas of the curved leg contact the ground, they behave differently in applying physical parameters like stiffness and free leg-length. After finding the optimal parameter coupling of the curved leg and the optimal constant parameters of a straight leg, we designed them, and 3D printed the leg shapes. Testing them in experiments, the optimal curved leg is 40% better in performance compared with the straight leg.