Integration of A-Star Search and Classic Optimal Control for Safe Planning of Continuum Deformation of a Multi-Quadcopter System

TL;DR

This paper presents a decentralized algorithm combining continuum mechanics, A-Star search, and optimal control to safely and efficiently plan the continuum deformation of a multi-quadcopter system navigating obstacle-rich environments.

Contribution

It introduces a novel integration of continuum mechanics, A-Star search, and optimal control for decentralized multi-quadcopter deformation planning.

Findings

Successfully plans safe continuum deformation in obstacle environments.

Minimizes travel distance of leader quadcopters.

Ensures decentralized coordination through local communication.

Abstract

This paper offers an algorithmic approach to plan continuum deformation of a multi-quadcopter system (MQS) in an obstacle-laden environment. We treat the MQS as finite number of particles of a deformable body coordinating under a homogeneous transformation. In this context, we define the MQS homogeneous deformation coordination as a decentralized leader-follower problem, and integrate the principles of continuum mechanics, A-Star search method, and optimal control to safety and optimally plan MQS continuum deformation coordination. In particular, we apply the principles of continuum mechanics to obtain the safety constraints, use the A-Star search method to assign the intermediate configurations of the leaders by minimizing the travel distance of the MQS, and determine the leaders' optimal trajectories by solving a constrained optimal control problem. The optimal planning of the continuum deformation coordination is acquired by the quadcopter team in a decentralized fashion through local communication.