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

Mahmud, Mohd Saiful Azimi; Abidin, Mastura Shafinaz Zainal; Mohamed, Zulkifli; Rahman, Muhammad Khairie Idham Abd; Iida, Michihisa

doi:10.1016/j.compag.2019.01.016

Cited by 86 publications

(45 citation statements)

References 11 publications

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“…To validate the proposed algorithm, which facilitates both global and local planning, five case studies were investigated focusing on the minimization of: (i) the distance travelled in the crop headlands using different turning radii; (ii) the input cost and required time for a fleet of homogeneous vehicles; (iii) the input cost for the required time and both criteria for a fleet of both homogeneous; and (iv) heterogeneous vehicles with small tanks; and (v) the time for a fleet of homogeneous UGVs in a field divided into three parcels. Finally, the work presented in [46] developed a multi-objective path planner for a mobile robot in greenhouse environments. The developed algorithm considered travelling distance and routing angel subject to pesticide tank capacity constraints, and it was tested against four alternative routing test cases.…”

Section: Reviewmentioning

confidence: 99%

Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects

et al. 2020

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The advent of mobile robots in agriculture has signaled a digital transformation with new automation technologies optimize a range of labor-intensive, resources-demanding, and time-consuming agri-field operations. To that end a generally accepted technical lexicon for mobile robots is lacking as pertinent terms are often used interchangeably. This creates confusion among research and practice stakeholders. In addition, a consistent definition of planning attributes in automated agricultural operations is still missing as relevant research is sparse. In this regard, a “narrative” review was adopted (1) to provide the basic terminology over technical aspects of mobile robots used in autonomous operations and (2) assess fundamental planning aspects of mobile robots in agricultural environments. Based on the synthesized evidence from extant studies, seven planning attributes have been included: (i) high-level control-specific attributes, which include reasoning architecture, the world model, and planning level, (ii) operation-specific attributes, which include locomotion–task connection and capacity constraints, and (iii) physical robot-specific attributes, which include vehicle configuration and vehicle kinematics.

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Section: Reviewmentioning

confidence: 99%

Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects

et al. 2020

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“…It is used for shortest path problem in graph theory (30). It was commonly utilized to find the navigation cost which is the smallest value by the shortest path planning (31). It is mostly applicable to for use in singlesource shortest path problem.…”

Section: A Dijkstra Algorithmmentioning

confidence: 99%

Automated Guided Vehicle Routing: Static, Dynamic and Free range

Hasan¹,

Abidin²,

Said³

2019

IJEAT

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Nowadays, automated guided vehicles (AGV) play very important role in modern factory automations. The AGV systems provide efficient routing for material flow and distribution among workstations at the exact time and place. Routing of AGV is the process of determining routes to fulfill their respective transport jobs. The routing problem of AGV in production system can be studied as a shortest path problem on a transfer network. It aims to find the shortest path between two vertices or nods. Most transport systems using AGV are centrally controlled and use static routing (pre-defined routes), which follows fixed line. Instead of using fixed path, dynamic routing for AGV can be used to add a high flexibility to the system. To accommodate the increased flexibility and reduced time, new operational controllers using Labview software must be able to adapt to small deviations. In this paper, routing of AGV, different AGV shortest path algorithms such as Dijkstra algorithm, A-star algorithm, Short Path Problem with Time Window (SPPTW), hybrid partial swarm optimization and genetic algorithm PSOGA are discussed with highlights of their main differences and comparison between them. AGV Scheduling is presented. In addition, the controller developed within Labview environment directs an AGV in real time using local position system are achieved.

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“…Another multi-objective path planner system was suggested, in which the problem of spraying pesticides in greenhouses was addressed as a vehicle routing issue [11]. The probabilistic roadmap path planner was designed to solve the vehicle routing problem, and the routes are generated between the plants for spraying pesticides based on the virtual environment.…”

Section: Introductionmentioning

confidence: 99%

An IoT- Enabled Augmented Reality Framework for Plant Disease Detection

Ponnusamy¹,

Natarajan²,

Ramasamy³

et al. 2021

RIA

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Augmented reality system enables effective interaction with field view data and executes a particular task effectively by visual display aid. Precision agriculture involves precision measurement, data generation, analysis for interpretation of data, and decision-making to improve the yield and monitor the plant. Augmented reality will help to systematically acquire the needed data and interpret the required information from the analytical result on the field. This paper presents a low-cost development of the augmented reality system for on-field analysis of plant diseases. The article also presents a framework of deep learningbased cloud data analytic to enable on-field real-time interaction between the farmers and cloud data processing systems using a head-mounted unit. The proposed augmented reality system performance is validated for its accuracy in detecting plant diseases, real-time interaction response time, and ease of usage by the farmer community. The results show that the proposed mechanism will be able to produce real-time augment interaction to the farmer for the task of disease inspection of the plant effectively and accurately.

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

Cited by 86 publications

References 11 publications

Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects

Mobile Robotics in Agricultural Operations: A Narrative Review on Planning Aspects

Automated Guided Vehicle Routing: Static, Dynamic and Free range

An IoT- Enabled Augmented Reality Framework for Plant Disease Detection

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