Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
Robot Motion Planning
Multiagent Robotic Systems
Parallel Substitution Algorithm: Theory and Application
Parallel Substitution Algorithm: Theory and Application
A directional diffusion algorithm on cellular automata for robot path-planning
Future Generation Computer Systems - Cellular automata CA 2000 and ACRI 2000
Fuzzy Motion Planning of Mobile Robots in Unknown Environments
Journal of Intelligent and Robotic Systems
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Automatic Panoramic Image Stitching using Invariant Features
International Journal of Computer Vision
Theta*: any-angle path planning on grids
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Design and implementation of a fuzzy-modified ant colony hardware structure for image retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Path-Planning for multiple generic-shaped mobile robots with MCA
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Coordinated multi-robot exploration
IEEE Transactions on Robotics
Queues and Artificial Potential Trenches for Multirobot Formations
IEEE Transactions on Robotics
Human-robot interaction in rescue robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Classification With Ant Colony Optimization
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A neural network approach to complete coverage path planning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An efficient dynamic system for real-time robot-path planning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A MAP Approach for Joint Motion Estimation, Segmentation, and Super Resolution
IEEE Transactions on Image Processing
A morphogenetic approach to flexible and robust shape formation for swarm robotic systems
Robotics and Autonomous Systems
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Creating collision-free trajectories for mobile robots, known as the path planning problem, is considered to be one of the basic problems in robotics. In case of multiple robotic systems, the complexity of such systems increases proportionally with the number of robots, due to the fact that all robots must act as one unit to complete one composite task, such as retaining a specific formation. The proposed path planner employs a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every robot of a team while their formation is kept immutable. The method reacts with obstacle distribution changes and therefore can be used in dynamical or unknown environments, without the need of a priori knowledge of the space. The team is divided into subgroups and all the desired pathways are created with the combined use of a CA path planner and an ACO algorithm. In case of lack of pheromones, paths are created using the CA path planner. Compared to other methods, the proposed method can create accurate collision-free paths in real time with low complexity while the implemented system is completely autonomous. A simulation environment was created to test the effectiveness of the applied CA rules and ACO principles. Moreover, the proposed method was implemented in a system using a real world simulation environment, called Webots. The CA and ACO combined algorithm was applied to a team of multiple simulated robots without the interference of a central control. Simulation and experimental results indicate that accurate collision free paths could be created with low complexity, confirming the robustness of the method.