Intelligent planning and control for multirobot coordination: An event-based approach

TLDR

Event‑based planning and control theory is introduced as the foundational framework. The paper proposes a new planning and control scheme for multirobot coordination. The scheme designs an event‑based motion reference that drives the multirobot system toward optimal coordination, employing hybrid position/force controllers built on task‑space nonlinear feedback linearization, incorporating joint motor dynamics and redundancy‑aware task projection, and is implemented via a distributed parallel computing architecture. Experimental tests on two 6‑DOF PUMA 560 robots demonstrated very good coordination results.

Abstract

A new planning and control scheme for multirobot coordination is presented. First, the event-based planning and control theory is introduced. The most important step is the design of an event-based motion reference for the multirobot system. It drives the system to achieve the best possible coordination. Hybrid position/force controllers which are able to perform a large class of tasks are designed based on the combination of general task space with the well-known nonlinear feedback linearization technique. To improve the force control performance, the dynamics of joint motors have been considered in the force control. For a given task, a task projection operator can be found for each robot with the consideration of redundancy management. It projects the feedback linearized model to the actual task space. A distributed computing architecture is proposed to implement this scheme in a parallel computation. The event-based coordination scheme was experimentally implemented and tested for the coordinated control of two 6 DOF PUMA 560 robots with very good results.