Research on Multiobjective Optimization Algorithm for Cooperative Harvesting Trajectory Optimization of an Intelligent Multiarm Straw-Rotting Fungus Harvesting Robot

Shuzhen Yang, Bocai Jia, Tao Yu and Jin Yuan
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Shuzhen Yang: School of Intelligent Manufacturing and Control Engineering, Shanghai Polytechnic University, Shanghai 201209, China
Bocai Jia: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Tao Yu: School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Jin Yuan: College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China

Agriculture, 2022, vol. 12, issue 7, 1-24

Abstract: In view of the difficulties of fruit cluster identification, the specific harvesting sequence constraints of aggregated fruits, and the balanced harvesting task assignment for the multiple arms with a series-increasing symmetric shared (SISS) region, this paper proposes a multi-objective optimization algorithm, which combines genetic algorithm (GA) and ant colony optimization (ACO) stepwise, to optimize the multiarm cooperative harvesting trajectory of straw-rotting fungus to effectively improve the harvesting efficiency and the success rate of non-destructive harvesting. In this approach, firstly, the multiarm trajectory optimization problem is abstracted as a multiple travelling salesman problem (MTSP). Secondly, an improved local density clustering algorithm is designed to identify the cluster fruits to prepare data for harvesting aggregated fruits in a specific order later. Thirdly, the MTSP has been decomposed into M independent TSP (traveling salesman problem) problems by using GA, in which a new DNA (deoxyribonucleic acid) assignment rule is designed to resolve the problem of the average distribution of multiarm harvesting tasks with the SISS region. Then, the improved ant colony algorithm, combined with the auction mechanism, is adopted to achieve the shortest trajectory of each arm, which settles the difficulty that the clustered mature fruits should be harvested in a specified order. The experiments show that it can search for a relatively stable optimal solution in a relatively short time. The average harvesting efficiency is up to 1183 pcs/h and the average harvesting success rate is about 97%. Therefore, the proposed algorithm can better plan the harvesting trajectory for multiarm intelligent harvesting, especially for areas with many aggregated fruits.

Keywords: straw-rotting fungus; multiarm harvesting trajectory optimization; multiobjective optimization; cluster fruit; genetic ant colony stepwise algorithm (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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