Multi-agent planning for coordinated robotic weed killing

This work presents a strategy for coordinated multi-agent weeding under conditions of partial environmental information. Our goal is to demonstrate the feasibility of coordination strategies for improving the weeding performance of autonomous agricultural robots. We show that, given a sufficient number of agents, the algorithm can successfully weed fields with various initial seed bank densities, even when multiple days are allowed to elapse before weeding commences. Furthermore, the use of coordination between agents is demonstrated to strongly improve system performance as the number of agents increases, enabling the system to eliminate all the weeds in the field, as in the case of full environmental information, when the planner without coordination failed to do so. As a domain to test our algorithms, we have developed an open source simulation environment, Weed World, which allows real-time visualization of coordinated weeding policies, and includes realistic weed generation. In this work, experiments are conducted to determine the required number of agents and their required transit speed, for given initial seed bank densities and varying allowed days before the start of the weeding process.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2018

Author dc:creator

• McAllister, Wyatt Spalding

Contributors dc:contributor

• Chowdhary, Girish

• Multi-Robot Coordination, Multi-Agent Planning, Agricultural Robotics

Statement dc:rights

• 2018 Wyatt McAllister

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/101286

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/101286