A Methodology to Characterize an Optimal Robotic Manipulator Using PSO and ML Algorithms for Selective and Site-Specific Spraying Tasks in Vineyards

A Methodology to Characterize an Optimal Robotic Manipulator Using PSO and ML Algorithms for Selective and Site-Specific Spraying Tasks in Vineyards

This paper presents an improved methodology for characterizing task-oriented optimal manipulator configuration, tested on a case study of selective spraying in vineyards. It compares the current approach for optimizing manipulator configurations, which relies on simulation and optimization algorithm...

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Bibliographic Details
Main Authors: Roni Azriel, Oded Degani, Avital Bechar
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Robotics
Subjects:
robotic manipulator
optimal design
simulation
particle swarm optimization
machine learning
spraying task
Online Access:https://www.mdpi.com/2218-6581/14/5/58
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