Towards Optimized Distributed Multi-Robot Printing: An Algorithmic Approach

TL;DR

This paper introduces an optimization-based distributed multi-robot printing method that decomposes images into geodesic cells for efficient task allocation and verifies the approach with a custom robot prototype.

Contribution

It proposes a novel task decomposition and allocation algorithm for multi-robot printing and demonstrates its effectiveness with a custom-designed spraying robot.

Findings

The algorithm effectively decomposes images into rasterized geodesic cells.

Experimental results show reduced printing time with the proposed method.

The designed robot successfully implements the printing process on smooth surfaces.

Abstract

This paper presents a distributed multi-robot printing method which utilizes an optimization approach to decompose and allocate a printing task to a group of mobile robots. The motivation for this problem is to minimize the printing time of the robots by using an appropriate task decomposition algorithm. We present one such algorithm which decomposes an image into rasterized geodesic cells before allocating them to the robots for printing. In addition to this, we also present the design of a numerically controlled holonomic robot capable of spraying ink on smooth surfaces. Further, we use this robot to experimentally verify the results of this paper.