Quadratic Programming for Multirobot and Task-Space Force Control

TLDR

The study proposes assembling multiple robot models and their interaction constraints into a single quadratic program to enable centralized multirobot control. The method models each robot (or cluster) and its interactions as a unified QP, computing cluster states and contact forces consistently, and is validated on diverse real robotic platforms. Extending task‑space QP controllers to multirobot systems simplifies task specification and enables centralized control across a range of complex robotic platforms.

Abstract

We have extended the task-space multiobjective controllers that write as quadratic programs (QPs) to handle multirobot systems as a single centralized control. The idea is to assemble all the “robots” models and their interaction task constraints into a single QP formulation. By multirobot, we mean that whatever entities a given robot will interact with (solid or articulated systems, actuated, partially or not at all, fixed-base or floating-base), we model them as clusters of robots and the controller computes the state of each cluster as an overall system and their interaction forces in a physically consistent way. By doing this, the tasks specification simplifies substantially. At the heart of the interactions between the systems are the contact forces; methodologies are provided to achieve reliable force tracking by our multirobot QP controller. The approach is assessed by a large panel of experiments on real complex robotic platforms (full-size humanoid, dexterous robotic hand, fixed-base anthropomorphic arm) performing whole-body manipulations, dexterous manipulations, and robot-robot comanipulations of rigid floating objects and articulated mechanisms, such as doors, drawers, boxes, or even smaller mechanisms like a spring-loaded click pen.