In this paper, a probabilistic roadmap planner algorithm with the multi robot path planning problem have been proposed by using the A* search algorithm in a dynamic environment. The whole process consists of two phases. In the first phase: Preprocessing phase, the work space is converted into the configuration space, constructing a probabilistic roadmap graph in the free space, and finding the optimal path for each robot using a global planner that avoids the collision with the static obstacles. The second phase: Moving phase, moves each robot in a prioritized manner from its starting point to its ending point through a near optimal path with avoiding collision with the moving obstacles and the other robots. A comparison has been done with the depth first algorithm to see the difference. The simulation results shows that choosing A* search algorithm affect positively the speed of the two phases together in comparison to the depth first search algorithm. General TermsArtificial intelligence, Robot path planning.

In this paper a proposed method to encrypt images based Liu Hyper Chaotic System (LHCS) is presented. In the proposed algorithm is used to generate a key for diffusion process, to confuse relationships between the input image and encrypted image. Besides of the four initial state (initial keys) in LHCS, six control parameters were used to increase the key space. Simulation results show that the proposed method has large key space (key space is 10 70 ), and it is responsive to a trivial change of the key. Therefore it with stands different types of attacks such as brute force, differential, and chosen-cipher text attacks.

A proposed method of path planning for single mobile robot in2D envir on ment Cluttered with moving obstacles. The propose dmethod supposes mobile robot and obsta clesare the same specifications interms of speed and movement and having the same goal. The robot moving fromone place to anothertoreachthegoal based artificial fish swarm algorithm. The simulation of the method show that the proposed method find the optimal (near optimal) path. The proposed method is complete becauseit find the path, ifany.