Quadratic Programming Optimization for Bio-Inspired Thruster-Assisted Bipedal Locomotion on Inclined Slopes

TL;DR

This paper introduces a quadratic programming-based control method for a bipedal robot with thrusters, enabling effective slope walking by integrating posture manipulation and thrust vectoring inspired by nature.

Contribution

It develops and implements a novel QP-based control framework for thruster-assisted bipedal locomotion on inclined slopes, expanding the capabilities of existing dynamic walking controllers.

Findings

Successful simulation of thruster-assisted slope walking

Enhanced stability and adaptability in inclined terrains

Demonstration of the control method's effectiveness in dynamic scenarios

Abstract

Our work aims to make significant strides in understanding unexplored locomotion control paradigms based on the integration of posture manipulation and thrust vectoring. These techniques are commonly seen in nature, such as Chukar birds using their wings to run on a nearly vertical wall. In this work, we show quadratic programming with contact constraints which is then given to the whole body controller to map on robot states to produce a thruster-assisted slope walking controller for our state-of-the-art Harpy platform. Harpy is a bipedal robot capable of legged-aerial locomotion using its legs and thrusters attached to its main frame. The optimization-based walking controller has been used for dynamic locomotion such as slope walking, but the addition of thrusters to perform inclined slope walking has not been extensively explored. In this work, we derive a thruster-assisted bipedal walking with the quadratic programming (QP) controller and implement it in simulation to study its performance.