Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment

•An implementation of NSGA-III in spraying operation is presented in this paper.•The algorithm was implemented in a real-like virtual platform.•Some constraints are considered based on spraying capacity and navigation requirement.•The proposed method performing well compared to NSGA-II. Robotics in...

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Bibliographic Details
Published in:Computers and electronics in agriculture 2019-02, Vol.157, p.488-499
Main Authors: Mahmud, Mohd Saiful Azimi, Abidin, Mohamad Shukri Zainal, Mohamed, Zaharuddin, Rahman, Muhammad Khairie Idham Abd, Iida, Michihisa
Format: Article
Language:English
Subjects:
Agricultural management
Agricultural operation
Classification
Cost engineering
Genetic algorithms
Greenhouses
Mobile robot
Multi-objective
Multiple objective analysis
Navigation
Operations research
Path planning
Pesticides
Robotics
Robots
Route planning
Soil conditions
Sorting algorithms
Spraying
Vehicle routing
Virtual environments
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Summary:•An implementation of NSGA-III in spraying operation is presented in this paper.•The algorithm was implemented in a real-like virtual platform.•Some constraints are considered based on spraying capacity and navigation requirement.•The proposed method performing well compared to NSGA-II. Robotics in agriculture has experienced enormous development in the past decade. In order to accomplish numerous agricultural tasks, the order in which the crop is covered is particularly important in order to minimise travelling cost and to preserve soil conditions. However, it is difficult to determine an optimised sequential path for the robot which minimizes navigation costs, while ensuring a fully completed agricultural operation. This paper presents the implementation of a multi-objective algorithm to solve the path planning problem for pesticide spraying operation inside a greenhouse. Pesticide spraying problems found in greenhouses have been adapted from the vehicle routing problem found in operations research, where the infected plants represent the customers and the mobile robot represents the vehicles. Routes between the plants are generated using a Probabilistic Roadmap path planner based on the designed virtual environment. The virtual environment is designed based on the real greenhouse environment to visualise the agricultural operation inside the greenhouse. To determine the best routes for the mobile robot, the Non-dominated Sorting Genetic Algorithm using Reference Point Based (NSGA-III) is tested and applied to the system. The solution quality has been compared with the Non-dominated Sorting Genetic Algorithm (NSGA-II) using the C-metric indicator. Comparisons with NSGA-II using the C-metric indicator verify that NSGA-III offers a superior performance with a good quality result.
ISSN:0168-1699
1872-7107
DOI:10.1016/j.compag.2019.01.016