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In this paper, A solution is proposed for the multi-robot task assignment in obstacle environment, which combines the A∗ algorithm with the genetic algorithm. Our main work are twofold:(a) Path planning method based on A∗ algorithm to search an optimal path between any robot and any target or any two targets; and (b) task assignment method based on the genetic algorithm for the assignment of robots...
The aim of the paper is research and comparative analysis of algorithms from the field of artificial intelligence for searching shortest path in a maze. The algorithms studied are A∗ (A star), backtracking algorithm and genetic algorithm (GAPP — Genetic Algorithm Path Planning). The algorithms are compared by two criteria: length of the found path and time for finding the path. The results, presented...
We discuss a scheduling problem for a two-machine robotic flow-shop with a bounded intermediate station and robots which is realistic in FMCs (flexible manufacturing cells). The problem asks to minimize the total weighted completion time. It is NP-hard. In this paper, we propose a heuristic algorithm based on GA (Genetic Algorithm) which is applicable to the problem, and which allows not only permutation,...
A novel progressive genetic algorithm is developed for motion planning of a three-limbed robot. The proposed motion planning method can be used to find a optimal joints trajectory from the initial to the final position and orientation. On the basis of the genetic algorithm a kind of variable structure genetic algorithm is proposed to solve the problem of motion planning of the three-limbed in dynamic...
This paper presents the application of genetic algorithm (ga) and ant colony optimization (ACO) algorithm for robot path planning (RPP) in global static environment. Both algorithms were applied within global maps that consist of different number of free space nodes. These nodes generally represent the free space extracted from the robot map. Performances between both algorithms were compared and...
A path planning algorithm of robot is proposed based on ensemble algorithm of the learning classifier system, which design fitness function in dynamic environment. The paper derived and proved that ensemble algorithm is convergence and provided a theoretical guarantee for the path planning algorithm. Simulation results also showed that genetic algorithms and learning classifier system combination...
To overcome the defects of precocity and the time for initial population building is too long in traditional augment ant colony algorithm for mobile robot global path planning, an improved augment ant colony algorithm is presented in this paper. The operations of crossover and mutation of genetic algorithm (GA) are used in augment ant colony optimization, and the heuristic probability function is...
In this paper, we present an optimum approach to design a MIMO controller for a manipulator using discrete tabu search (TS) algorithm. In the first step, the TS algorithm is reviewed and then we employ the proposed method in order to assign efficiently the optimal PID controller parameters. The design goal is to minimize the integral absolute error and reduce transient response by minimizing overshoot,...
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