On Optimising Topology of Agricultural Fields for Efficient Robotic Fleet Deployment

Zhu, Zuyuan, Das, Gautham and Hanheide, Marc (2023) On Optimising Topology of Agricultural Fields for Efficient Robotic Fleet Deployment. In: The 18th international conference on Intelligent Autonomous System 2023 (IAS18 – 2023), July 4-7, 2023, Sowon, Korea.

On Optimising Topology of Agricultural Fields for Efficient Robotic Fleet Deployment
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Item Type:Conference or Workshop contribution (Presentation)
Item Status:Live Archive


Field-deployed robotic fleets can provide solutions that improve operational efficiency, control operational costs, and provide farmers with transparency over the day-to-day operations with scouting operations. The topology of agricultural farms such as polytunnels provides a basic environmental configuration that can be exploited to create a topological map to aid operational planning and robot navigation. However, these environments are optimised for operations by humans or for large farming vehicles and pose a major challenge for multiple moving robots to coordinate their navigation while performing tasks. The farm environment without any topological modifications for supporting robotic fleet deployments can cause traffic bottlenecks, eventually affecting the overall efficiency of the fleet. In this work, we propose a Genetic Algorithm-based Topological Optimisation (GATO) algorithm that discretises the search space of topological modifications into finite integer combinations. Each solution is encoded as an integer vector that contains the location information of the topology modification. The algorithm is evaluated in a discrete event simulation of the picking and in-field logistics process in a commercial strawberry farm and the results validate the effectiveness of our algorithm in identifying the topological modifications that improve the efficiency of the robotic fleet operations.
robot traffic planning, multi-robot systems, agri-robotics, topological optimisa-
tion, discrete event simulation, genetic algorithm

Keywords:Multi-robot systems, Agri-robotics, Discrete event simulation, Topological optimisation, Robot traffic planning, Genetic Algorithms
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G200 Operational Research
Divisions:COLLEGE OF HEALTH AND SCIENCE > Lincoln Institute for Agri-Food Technology
ID Code:55464
Deposited On:15 Sep 2023 10:20

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