The complexity of robot motion planning
The complexity of robot motion planning
Robot Motion Planning
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
A novel algorithm for the coordination of multiple mobile robots
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
Path-Planning for multiple generic-shaped mobile robots with MCA
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Roadmap-based motion planning in dynamic environments
IEEE Transactions on Robotics
Autonomous robot navigation using adaptive potential fields
Mathematical and Computer Modelling: An International Journal
A new reactive target-tracking control with obstacle avoidance in a dynamic environment
ACC'09 Proceedings of the 2009 conference on American Control Conference
International Journal of Automation and Computing
Local, self-organizing strategies for robotic formation problems
ALGOSENSORS'11 Proceedings of the 7th international conference on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities
Continuous local strategies for robotic formation problems
SEA'12 Proceedings of the 11th international conference on Experimental Algorithms
A hybrid navigation strategy for multiple mobile robots
Robotics and Computer-Integrated Manufacturing
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An efficient, simple, and practical real time path planning method for multiple mobile robots in dynamic environments is introduced. Harmonic potential functions are utilized along with the panel method known in fluid mechanics. First, a complement to the traditional panel method is introduced to generate a more effective harmonic potential field for obstacle avoidance in dynamically changing environments. Second, a group of mobile robots working in an environment containing stationary and moving obstacles is considered. Each robot is assigned to move from its current position to a goal position. The group is not forced to maintain a formation during the motion. Every robot considers the other robots of the group as moving obstacles and hence the physical dimensions of the robots are also taken into account. The path of each robot is planned based on the changing position of the other robots and the position of stationary and moving obstacles. Finally, the effectiveness of the scheme is shown by modeling an arbitrary number of mobile robots and the theory is validated by several computer simulations and hardware experiments.