No abstract

Footstep and path planning for dynamic legged robots is complex, and even if such a plan exists, execution is even harder. We propose a new method for a planar model of a dynamic legged robot that brings the trajectory to an absolute desired destination even on unknown rough terrain with minimal sensing. This can later aid a global planner to reach “way-points” with low destination errors. The basic block of the technique incorporates two consecutive jumps, each triggers a minimalistic control method to govern a sole controller—the leg angle during flight. Only two detection sensors and initial state information are required during implementation. Prior to execution, an optimization process is initiated to obtain the temporal control laws for both jumps. This work presents the process of obtaining the control parameters and studies the performance and limitations of the scheme.

No abstract

No abstract

The superior ability of dynamic legged locomotion in traversing rough terrain relative to wheeled or tracked mechanisms comes with the cost of fragile stability. Simple control methods that use only a few basic detection sensors and apply a single controller help robots keep their balance when traversing unforeseen rough terrain. Exploiting multiple controllers simultaneously, such as the free leg length and stiffness in our hopping monopod, can further improve robustness but is often mechanically hard to implement. This work demonstrates that a curved leg shape can improve the robustness of a robot to perturbations in both terrain levels and initial horizontal velocity without complicating the control scheme. Our work develops Spring Loaded Inverted Pendulum (SLIP) based models that manifest the coupling of the leg’s parameters and capture the rolling motion. We use these models to find an optimal combination of parameters that maximizes a measure for long-term stability – reaching a desired relative height above terrain. We demonstrate that when traversing unknown rough terrain, such optimal coupling can increase robustness to perturbations in the initial horizontal velocity by 93% relative to the optimal conventional SLIP model. We further demonstrate our results in experiments.