The Path Planning of Agricultural AGV in Potato Ridge Cultivation

Mai, Tongning; Shao, Shiquan; Yun, Zehui

doi:10.22606/as.2019.32003

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…In [65], the authors proposed a path planning method inspired by the Ant Colony Optimization (ACO) algorithm to multipoint measurements in potato ridge cultivation. However, the related method did not perform successfully in finding optimal paths and is also useful for 2D areas.…”

Section: Path Planning In Agricultural Applicationsmentioning

confidence: 99%

Adaptive Metaheuristic-Based Methods for Autonomous Robot Path Planning: Sustainable Agricultural Applications

et al. 2022

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The increasing need for food in recent years means that environmental protection and sustainable agriculture are necessary. For this, smart agricultural systems and autonomous robots have become widespread. One of the most significant and persistent problems related to robots is 3D path planning, which is an NP-hard problem, for mobile robots. In this paper, efficient methods are proposed by two metaheuristic algorithms (Incremental Gray Wolf Optimization (I-GWO) and Expanded Gray Wolf Optimization (Ex-GWO)). The proposed methods try to find collision-free optimal paths between two points for robots without human intervention in an acceptable time with the lowest process costs and efficient use of resources in large-scale and crowded farmlands. Thanks to the methods proposed in this study, various tasks such as tracking crops can be performed efficiently by autonomous robots. The simulations are carried out using three methods, and the obtained results are compared with each other and analyzed. The relevant results show that in the proposed methods, the mobile robots avoid the obstacles successfully and obtain the optimal path cost from source to destination. According to the simulation results, the proposed method based on the Ex-GWO algorithm has a better success rate of 55.56% in optimal path cost.

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Section: Path Planning In Agricultural Applicationsmentioning

confidence: 99%

Adaptive Metaheuristic-Based Methods for Autonomous Robot Path Planning: Sustainable Agricultural Applications

et al. 2022

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“…The goal of this work is to navigate around an unknown oil palm plantation [87]. In an unstructured 3D terrain, an artificial potential field planner is used for energy optimization [88], and Mai et al [89] employs multi-point measurement in potato cultivation using ACO. The authors differ on which approach to employ for point-to-point path routing, despite the fact that cell decomposition is marginally preferred.…”

Section: Application Of Routing In Agriculturementioning

confidence: 99%

A Comprehensive Review of Path Planning for Agricultural Ground Robots

et al. 2022

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The population of the world is predicted to reach nine billion by 2050, implying that agricultural output must continue to rise. To deal with population expansion, agricultural chores must be mechanized and automated. Over the last decade, ground robots have been developed for a variety of agricultural applications, with autonomous and safe navigation being one of the most difficult hurdles in this development. When a mobile platform moves autonomously, it must perform a variety of tasks, including localization, route planning, motion control, and mapping, which is a critical stage in autonomous operations. This research examines several agricultural applications as well as the path planning approach used. The purpose of this study is to investigate the current literature on path/trajectory planning aspects of ground robots in agriculture using a systematic literature review technique, to contribute to the goal of contributing new information in the field. Coverage route planning appears to be less advanced in agriculture than point-to-point path routing, according to the finding, which is due to the fact that covering activities are usually required for agricultural applications, but precision agriculture necessitates point-to-point navigation. In the recent era, precision agriculture is getting more attention. The conclusion presented here demonstrates that both field coverage and point-to-point navigation have been applied successfully in path planning for agricultural robots.

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“…This paper uses the minimum number of iterations after convergence to indicate the convergence speed of the algorithm. The smaller the minimum number of iterations after convergence, the faster the convergence speed of the algorithm [14].…”

Section: Introductionmentioning

confidence: 99%

Research on Multi-AGVs Path Planning and Coordination Mechanism

et al. 2020

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Reasonable automatic guided vehicle path planning can shorten the transportation time of materials and improve the production efficiency of the intelligent assembly workshop. Ant colony algorithm is a widely used path planning method, however, it suffers from the shortcomings that being easy to fall into local optimum and low search efficiency. To overcome these shortcomings, first, this paper proposes a step optimization method to improve the search efficiency of the ant colony algorithm, and a path simplification method to avoid getting blindly tortuous paths; Second, to overcome the problem that the ant colony algorithm is easy to fall into the local optimum, this paper proposes an adaptive pheromone volatilization coefficient strategy, which uses different pheromone volatilization coefficients at different stages of the search path; third, for the path conflict problem of multiple automatic guided vehicles, this paper proposes a load balancing strategy to avoid it, which is based on the consideration that, path conflicts are caused by excessive concentration of multiple automatic guided vehicles paths. Extensive simulation results demonstrate the feasibility and efficiency of the proposed methods. INDEX TERMS ant colony algorithm, intelligent assembly, multiple automatic guided vehicles, path planning;

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The Path Planning of Agricultural AGV in Potato Ridge Cultivation

Cited by 5 publications

References 6 publications

Adaptive Metaheuristic-Based Methods for Autonomous Robot Path Planning: Sustainable Agricultural Applications

Adaptive Metaheuristic-Based Methods for Autonomous Robot Path Planning: Sustainable Agricultural Applications

A Comprehensive Review of Path Planning for Agricultural Ground Robots

Research on Multi-AGVs Path Planning and Coordination Mechanism

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