Robotic Mushroom Harvesting by Employing Probabilistic Road Map and Inverse Kinematics

Mohanan, M. G.; Salgaonkar, Ambuja

doi:10.54646/bijfrai.001

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…A mushroom harvesting robot (MHR) consists of three units: (i) a recognition system that identifies mature mushrooms and confirms their locations, (ii) a moving system with wheels that moves through the paths to reach the mature mushrooms, and (iii) picking system that grasps and plucks the mushrooms at the given location [86][87][88][89][90][91]146]. Assuming inputs from a recognition system, this paper presents and develops a novel robotic model to perform the moving and picking activities efficiently.…”

Section: Rmpde In Mushroom Harvestingmentioning

confidence: 99%

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Robotic Motion Planning in Dynamic Environments and its Applications

Mohanan

Salgaonkar

2022

IJRCS

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The fundamental problem of robot motion planning in a dynamic environment (RMPDE) is to find an optimal collision-free path from the start to the goal in a dynamic environment. Our literature survey of over 100 papers from the last four decades reveals that there are more than 30 models of RMPDE, and there is no benchmarking criterion to select one that is the best in a given situation. In this context, generating a regression-based model with 10 attributes is the first and foremost contribution of our research. Given a highly human-interactive environment like a cafeteria or a bus stand, the gross hidden Markov model has special importance for modeling a robot path. A variant of the growing hidden Markov model for a serving robot in a cafeteria is the second contribution of this paper. We simulated the behavior of GHMM in a cafeteria with static and dynamic obstacles (static obstacles were both convex and concave) and with three different arrangements of the tables and obstacles. Robots have been employed in mushroom harvesting. A novel proposition discussed in this paper is probabilistic road map planning for a robot that finds an optimum path for reaching the ripened mushrooms in a randomly planted mushroom farm and a dexterous hand to pluck the selected mushrooms by employing inverse kinematics. Further, two biologically inspired meta-heuristic algorithms, ant colony optimization, and firefly has been studied for their application to latex collection. The simulation results with this environment show that the firefly algorithm outperforms ant colony optimization in the general case. Finally, we have proposed a few pointers for future research in this domain. The compilation and comparison of various approaches to robot motion planning in highly dynamic environments, and the simulation of a few models for some typical scenarios, have been the contributions of this paper.

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Section: Rmpde In Mushroom Harvestingmentioning

confidence: 99%

“…where S and C represent the sine and cosine functions, by using (2), we can compute the joint angles, 𝜃1, 𝜃2, 𝜃3 [122][123][124][125][126]146].…”

Section: Denavit-hartenberg (Dh) Frame For Jointsmentioning

confidence: 99%

Robotic Motion Planning in Dynamic Environments and its Applications

Mohanan

Salgaonkar

2022

IJRCS

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“…[4] proposed the first selective harvesting robot for Agaricus bisporus, which made selective autonomous harvesting of straw-rotting fungus feasible. Since then, scholars have carried out many researches to on the edible fungus harvesting robot technology but mainly focused on visual recognition and endeffectors to improve the harvesting success rate [5][6][7][8][9][10][11][12][13], and few studies on trajectory planning. Yang [14] aimed at the issue of mushroom harvesting path planning.…”

Section: Introductionmentioning

confidence: 99%

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

Yang

Jia

et al. 2022

Agriculture

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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.

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Performance Analysis of Path Planning Algorithms for Fruit Harvesting Robot

Zeeshan

Aized

2023

J. Biosyst. Eng.

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Robotic Mushroom Harvesting by Employing Probabilistic Road Map and Inverse Kinematics

Cited by 4 publications

References 20 publications

Robotic Motion Planning in Dynamic Environments and its Applications

Robotic Motion Planning in Dynamic Environments and its Applications

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

Performance Analysis of Path Planning Algorithms for Fruit Harvesting Robot

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