Learning to Move a Robot with Random Morphology
Proceedings of the First European Workshop on Evolutionary Robotics
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A novel methodology for diversity preservation in evolutionary algorithms
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Fuzzy logic techniques for navigation of several mobile robots
Applied Soft Computing
Robotics and Autonomous Systems
On the design of an obstacle avoiding trajectory: Method and simulation
Mathematics and Computers in Simulation
A comparative study on some navigation schemes of a real robot tackling moving obstacles
Robotics and Computer-Integrated Manufacturing
Exploration of 2D and 3D Environments using Voronoi Transform and Fast Marching Method
Journal of Intelligent and Robotic Systems
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 04
Evolution of Fuzzy Controllers for Robotic Vehicles: The Role of Fitness Function Selection
Journal of Intelligent and Robotic Systems
Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning
Artificial Intelligence Review
Optimization using particle swarms with near neighbor interactions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
DYNAMIC ENVIRONMENT ROBOT PATH PLANNING USING HIERARCHICAL EVOLUTIONARY ALGORITHMS
Cybernetics and Systems
Robotic path planning using evolutionary momentum-based exploration
Journal of Experimental & Theoretical Artificial Intelligence
Disassembly Path Planning for Complex Articulated Objects
IEEE Transactions on Robotics
Physical Path Planning Using a Pervasive Embedded Network
IEEE Transactions on Robotics
Path planning of 3-D objects using a new workspace model
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Adaptive evolutionary planner/navigator for mobile robots
IEEE Transactions on Evolutionary Computation
New approach to intelligent control systems with self-exploring process
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The problem of robotic path planning has always attracted the interests of a significantly large number of researchers due to the various constraints and issues related to it. The optimisation in terms of time and path length and validity of the non-holonomic constraints, especially in large sized maps of high resolution, pose serious challenges for the researchers. In this paper we propose hybrid genetic algorithm particle swarm optimisation (HGAPSO) algorithm for solving the problem. Diversity preservation measures are introduced in this applied evolutionary technique. The novelty of the algorithm is threefold. Firstly, the algorithm generates paths of increasing complexity along with time. This ensures that the algorithm generates the best path for any type of map. Secondly, the algorithm is efficient in terms of computational time which is done by introducing the concept of momentum-based exploration in its fitness function. The indicators contributing to fitness function can only be measured by exploring the path represented. This exploration is vague at start and detailed at the later stages. Thirdly, the algorithm uses a multi-objective optimisation technique to optimise the total path length, the distance from obstacle and the maximum number of turns. These multi-objective parameters may be altered according to the robot design.