Grid-Based Mobile Robot Path Planning Using Aging-Based Ant Colony Optimization Algorithm in Static and Dynamic Environments.
Fatin Hassan Ajeil,Ibraheem Kasim Ibraheem,Ahmad Taher Azar,Ahmad Taher Azar,Amjad J. Humaidi +4 more
TLDR
Simulations showed that the proposed path planning algorithms result in superior performance by finding the shortest and the most free-collision path under various static and dynamic scenarios.Abstract:
Planning an optimal path for a mobile robot is a complicated problem as it allows the mobile robots to navigate autonomously by following the safest and shortest path between starting and goal points. The present work deals with the design of intelligent path planning algorithms for a mobile robot in static and dynamic environments based on swarm intelligence optimization. A modification based on the age of the ant is introduced to standard ant colony optimization, called modified aging ant colony optimization (AACO). The AACO was implemented in association with grid-based modeling for the static and dynamic environments to solve the path planning problem. The simulations are run in the MATLAB environment to test the validity of the proposed algorithms. Simulations showed that the proposed path planning algorithms result in superior performance by finding the shortest and the most free-collision path under various static and dynamic scenarios. Furthermore, the superiority of the proposed algorithms was proved through comparisons with other traditional path planning algorithms with different static environments.read more
Citations
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Improved Bat Algorithm for UAV Path Planning in Three-Dimensional Space
TL;DR: Based on the characteristics of the standard BA and the artificial bee colony algorithm (ABC), a new modification of the BA algorithm is proposed in this work, namely, the improved bat algorithm integrated into the ABC algorithm (IBA).
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3D Optical Machine Vision Sensors With Intelligent Data Management for Robotic Swarm Navigation Improvement
Oleg Sergiyenko,Vera Tyrsa +1 more
TL;DR: The algorithm of data transfer from 3D optical sensor, based on the principle of dynamic triangulation, uses the distributed scalable big data storage and artificial intelligence in automated 3D metrology to optimize the fused data base for better path planning.
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A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles.
Amjad J. Humaidi,Ibraheem Kasim Ibraheem,Ahmad Taher Azar,Ahmad Taher Azar,Musaab Esam Sadiq +4 more
TL;DR: The proposed optimal Adaptive Synergetic Controller (ASC) has been validated with a previous adaptive controller with the same robot structure and actuation, and it has been shown that the optimal ASC outperforms its opponent in terms of tracking speed and error.
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Computer vision-based high-quality tea automatic plucking robot using Delta parallel manipulator
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Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm.
TL;DR: Simulation results show that the multi-population migration genetic algorithm (MPMGA) is not only suitable for simulation maps of various scales and various obstacle distributions, but also has superior performance and effectively solves the problems of the standard genetic algorithm.
References
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Book
Ant Colony Optimization
TL;DR: Ant colony optimization (ACO) is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and of other animals as discussed by the authors In particular, ants have inspired a number of methods and techniques among which the most studied and the most successful is the general purpose optimization technique known as ant colony optimization.
Book
Engineering Optimization : Theory and Practice
TL;DR: This chapter discusses Optimization Techniques, which are used in Linear Programming I and II, and Nonlinear Programming II, which is concerned with One-Dimensional Minimization.
Book ChapterDOI
Ant Colony Optimization
TL;DR: Ant Colony Optimization (ACO) is a stochastic local search method that has been inspired by the pheromone trail laying and following behavior of some ant species as discussed by the authors.
Book
Nature-Inspired Optimization Algorithms
TL;DR: This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences, and researchers and engineers as well as experienced experts will also find it a handy reference.
Journal ArticleDOI
Genetic Algorithm Based Approach for Autonomous Mobile Robot Path Planning
TL;DR: The simulation results show that using GA with the improved crossover operators and the fitness function helps to find optimal solutions compared to other methods.