Generating Assistive Humanoid Motions for Co-Manipulation Tasks with a Multi-Robot Quadratic Program Controller

Abstract

Human-humanoid collaborative tasks require that the robot take into account the goals of the task, interaction forces with the human, and its own balance. We present a formulation for a real-time humanoid controller which allows the robot to keep itself balanced, while also assisting the human in achieving their shared objectives. We achieve this with a multi-robot quadratic program controller, which solves for human dynamics reconstruction and optimal robot controls in a single optimization problem. Our experiments on a simulated robot platform demonstrate the ability to generate interaction motions and forces that are similar to what a human collaborator would produce.