In this paper, a new method for path planning is proposed using a genetic algorithm (GA). Our method has two key advantages over existing GA methods. The first is a novel environment representation which allows a more efficient method for obstacles dilation in comparison to current cell based approaches that have a tradeoff between speed and accuracy. The second is the strategy we use to generate the initial population in order to speed up the convergence rate which is completely novel. Simulation results show that our method can find a near optimal path faster than computational geometry approaches and with more accuracy in smaller number of generations than GA methods.

Efficient and safe path planning for a Mobile Robot using genetic algorithm

In this paper, we propose a new method for mobile robot path planning in dynamic environment when the trajectories of obstacles are unknown. Our algorithm first utilizes a global approach called clearance based probabilistic roadmap method to find a suitable path and then locally apply evolutionary algorithm to keep the structure of the path when obstacles collide with the path. As a result, the path will act like an elastic band. To reach real time applicability, a light fitness function is proposed compare to other genetic algorithms to reduce the computation time needed for calculating and repairing path. Simulation results show that our method not only can keep the original structure of path, but also repair operation is done quickly even in the scenes with many obstacles.

Planning a robust path for mobile robots in dynamic environment

In this paper, two different important quality metrics, clearance and execution time, for motion planning of mobile robots are studied. Then a new approach, called clearance-based probabilistic roadmap method (CBPRM(c)), is proposed which in contrast to VV(c) method, visibility-Voronoi with clearance c, beside satisfaction of a predefined clearance is very efficient in running time. This provides the CBPRM(c) to be applicable in dynamic environments which require real-time approaches. Experiments showed that the CBPRM(c) is able to generate paths with very low execution time considering determined clearance.

A real-time Clearance-Based approach for motion planning of mobile robots

Overlay multicast has gained much attention in recent years as an alternative method to network layer multicast, especially for mobile ad hoc networks(MANETs). In this paper, we propose a new overlay multicast protocol to achieve simplicity of deployment, rapid adaptation of overlay structure when nodes move, and reduced delay. In our algorithm, to join or leave a multicast group, it is only sufficient for a member node to inform its first upstream member node. This updates the tree structure more rapidly when nodes move. In addition, join and leave delays are reduced and this makes the protocol suitable for multimedia multicasting in MANETs. Simulation results compared to that of ODMRP and ODOMP show that when the number of member nodes increases, our protocol outperforms ODOMP and when speed of nodes is high, it outperforms both ODOMP and ODMRP in terms of delivery ratio.

M. Naderan Tahan

Papers

A real-time Clearance-Based approach for motion planning of mobile robots

An Overlay Multicast Protocol for Multimedia Applications in Mobile Ad Hoc Networks