Tea Leaf Picking Path Planning Based on an Improved Ant Colony Optimization Algorithm
Journal Title: International Journal of Knowledge and Innovation Studies - Year 2025, Vol 3, Issue 1
Abstract
With the rapid advancement of modern robotics and artificial intelligence, intelligent picking robots have been widely adopted in agricultural production. Global path planning techniques have been applied to crop harvesting, such as oranges, apples, tea leaves, and tomatoes, yielding promising results. This study focuses on the path planning problem for a robotic arm used in premium tea leaf picking. Experimental simulations reveal that the Ant Colony Optimization (ACO) algorithm performs particularly well in solving small-scale Traveling Salesman Problems (TSP), as it can incrementally construct initial paths and, with properly tuned parameters, produce higher-quality solutions and achieve faster convergence compared to other algorithms. However, the traditional ACO algorithm tends to fall into local optima and suffers from slow convergence. To address these challenges, this paper proposes a dynamically optimized ACO algorithm that enhances the pheromone update rules and optimizes the α and β parameters during the search process. These parameters are updated according to the optimization results, and a ranking factor is introduced to prevent the optimal picking path from being overlooked. The proposed method demonstrates superior performance over the traditional ACO algorithm in terms of path quality and convergence speed.
Authors and Affiliations
Luqi Zhang
Keywords
Related Articles
- EP ID EP761828
- DOI https://doi.org/10.56578/ijkis030102
- Views 23
- Downloads 0
Selection of Enhanced Security Systems Using Complex T-Spherical Fuzzy Models Within a Complex Fuzzy Environment
The theory of Complex T-Spherical Fuzzy Sets (CTSpFSs) is introduced along with their Einstein operational methods under induced variables. This research aims to extend the theoretical framework of complex fuzzy sets (CF...
Application of Complex Polytopic Fuzzy Information Systems in Knowledge Engineering: Decision Support for COVID-19 Vaccine Selection
This paper aims to introduce the concepts of complex Polytopic fuzzy sets (CPoFSs) and complex Polytopic fuzzy numbers (CPoFNs), advancing the field of fuzzy logic. Three innovative aggregation operators based on CPoFNs...
Integration of Fuzzy Inference Systems and Linear Regression for Enhanced Height Prediction of Deodar Cedar Trees in Kumrat Valley
Accurate estimation of tree height is fundamental to sustainable forest management, particularly in regions such as Kumrat Valley, Pakistan, where Deodar Cedar (Cedrus deodara) serves as a vital ecological and economic r...
Enhanced Fault Diagnosis in Motor Bearings: Leveraging Optimized Wavelet Transform and Non-Local Attention
Recent advancements in non-destructive testing methodologies have significantly propelled the efficiency of bearing defect detection, vital for maintaining optimal final quality standards. This study introduces a novel a...
A Method for Creative Scheme Generation for Brand Design of Plush Toys Based on Extension Theory
In the era of branding, the design of plush toy brands often faces a contradiction with the needs of target user groups. Addressing the brand transformation challenges faced by small and micro enterprises in the plush to...