الفهرس 
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Abstract
Path planning plays an important role in robotics and the automation field in both static and dynamic environments. Many researchers have been working on this field since 1980. The pick and place process in the factories have been made in cooperation with the robots, which must be safe to operate with the human. Moreover, this involves both fast processing of the sensors data and fast and accurate to generate the optimum path based on the sensor’s data. This work describes the implementation of a path planner of a vertically articulated arm robot in 2-dimension static and dynamic environment, which can react with the change and the varying in environment. Therefore, to determine and explore the environment of the robot, a camera is use as a sensor to obstacles avoidance. The color detection techniques are considered here to track the obstacle motions. The aim of this work is to develop tools based on algorithms, for finding the optimal path from start to the goal without collision with obstacles subject to conditions such as time, path length, number of explored nodes and the number of the obstacles. The algorithms developed in this research make robotic motion more optimized. The A-star and wave-front with 2, 4 and 8-geomtry neighborhood algorithms are implemented for a seven degree-of -freedom arm robot and present some limitations and failures in many considered conditions. Hence the modified wave-front algorithm has been developed and created in this thesis to get a better response, which explore its wave from the target point due to the start point not the full workspace. Whereas, the modified wave-front algorithm with 8-geomtry neighborhood gives a satisfied result for the time and the path length. Finally, this algorithm is implemented by using a MATLAB software.