FUZZY-GENETIC ALGORITHMS AND TIME-OPTIMAL OBSTACLE-FREE PATH GENERATION FOR MOBILE ROBOTS

1999 ◽  
Vol 32 (1) ◽  
pp. 117-142 ◽  
Author(s):  
DILIP KUMAR PRATIHAR ◽  
KALYANMOY DEB ◽  
AMITABHA GHOSH
Keyword(s):  
Genetic Algorithms ◽  
Mobile Robots ◽  
Free Path ◽  
Path Generation ◽  
Time Optimal ◽  
Fuzzy Genetic

Comparative analysis of intelligent planning methods

2012 ◽  
Vol 9 (2) ◽  
pp. 53-57 ◽  
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov
Keyword(s):  
Neural Networks ◽  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Comparative Analysis ◽  
Mobile Robots ◽  
Sensory Information ◽  
Working Environment ◽  
Planning Methods ◽  
Intelligent Planning

The main stages of solving the problem of planning movements by mobile robots in a non-stationary working environment based on neural networks, genetic algorithms and fuzzy logic are considered. The features common to the considered intellectual algorithms are singled out and their comparative analysis is carried out. Recommendations are given on the use of this or that method depending on the type of problem being solved and the requirements for the speed of the algorithm, the quality of the trajectory, the availability (volume) of sensory information, etc.

Path Generation for Two Cooperative Puma Robots

1992 ◽  
Author(s):  
Jau-Liang Chen ◽  
Joseph Duffy
Keyword(s):  
Computer Graphics ◽  
Free Path ◽  
Path Generation ◽  
Final Destination ◽  
End Effectors

Abstract This paper describes the development of generating collision-free paths for a pair of cooperative PUMA robots as their end effectors grasp a workpiece in an obstacle-strewn environment. After the initial and goal positions of the wrist center are specified, a collision-free path for this pair of manipulators to move the workpiece safely to the final destination is generated. The algorithm is demonstrated via computer graphics animation on a Silicon Graphics IRIS 4D/70GT workstation.

Path Following System for Cooperative Mobile Robots

2010 ◽  
Vol 166-167 ◽  
pp. 161-166
Author(s):  
Ionut Dinulescu ◽  
Dorin Popescu ◽  
Mircea Nitulescu ◽  
Alice Predescu
Keyword(s):  
Artificial Intelligence ◽  
Mobile Robots ◽  
Path Following ◽  
Path Generation ◽  
Cooperative Robots ◽  
Generation System ◽  
Robot Systems ◽  
Simulation Results ◽  
Trajectory Generator

Recent advances in the domains of social and life artificial intelligence have constituted the basis for a new discipline that studies cooperation in multi-robot systems and its utility in applications where some tasks cannot be carried out by a single robot. This paper introduces a trajectory generator which is used for determination of the most appropriate trajectory which a robot needs to track in order to perform different tasks specific to cooperative robots, such as moving in a given formation or pushing an object to a given destination. Different algorithms are described in this paper, starting from simple polyline and circular paths to complex Bezier trajectories. Simulation results of the proposed path generation system are also provided, along with the description of its implementation on real mobile robots. An implementation of real robots is also presented in this paper.

Exploration path generation for multiple mobile robots using reaction-diffusion equation on a graph

2004 ◽  
Vol 11 (3) ◽  
pp. 195-212 ◽  
Author(s):  
Chomchana Trevai ◽  
Yusuke Fukazawa ◽  
Hideo Yuasa ◽  
Jun Ota ◽  
Tamio Arai ◽  
...  
Keyword(s):  
Diffusion Equation ◽  
Mobile Robots ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equation ◽  
Path Generation ◽  
Multiple Mobile Robots
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