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In this article, a new method for rapid tool movement in CNC machines is presented. Firstly, a single digital camera, installed on the Z-axis, captures the image of the workpiece on the work table. Image processing techniques, implemented using MATLAB, are then used to convert the image into a binary black and white image. This allows the locations of protruding edge sections on the workpiece, which could impede tool movement, to be identified. Quadtree decomposition is then performed on the binary image, and possible paths from the tool current location to its target location are found. These paths are then analysed based on the tool diameter clearance and the distance to the goal, and the shortest path with sufficient tool clearance is selected. A Visual Basic program then converts the selected path into G-code commands that provides instructions to the CNC machine tool such that this path is followed. With this method, the workpiece fixture location would not have to be precise as the imaging system would be able to automatically identify the target location with respect to the tool current location, along with the optimal path to reach it.

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Abstract. In this article, we used image processing by a webcam connected on top of the arm robot. The robot navigation is in an unknown environment. Then start point and target point were determined for the robot, so the robot needs to have a program for path planning using Voronoi diagrams to find the path. After the possible path for moving the robot was found, the route information obtained was sent to the arm robot. The arm robot moves in the workspace and any time new information was processed via the webcam. The program was written using MATLAB software which at controls the robot's movement the unknown environment. IntroductionAfter returned the manuscript must be appropriately modified. Today, vision based sensors such as webcams are falling in price more rapidly than any other sensors. This type of sensor is also a richer sensor than traditional ranging device, more data simultaneously [1]. Consequently, visual servo control of robotic manipulators has become an area of rapid research and development over the last two decades. Visual servo is the use of image data for manipulation and control of robot movement. Typically, the image of the robot workspace is captured, from which a target is identified. The position of the target is then estimated, and the corresponding robot joint angles and velocities are determined to enable the robot to reach its target. In this work, we present the development of a visual servo which enables a two-link planar robotic manipulator to navigate itself though arbitrarily positioned obstacles. The image of the workspace plane is captured using a webcam. The image is then processed to identify the edges of objects within the workspace. A Voronoi diagram (VD(S)) is then constructed, marking paths that avoid these objects. The optimal path is then computed, which would then be used as the robot trajectory. Processing Unknown Environment StrategyThis strategy can efficiently use the available information and reduce the planning time. Navigation in an unknown environment is a more challenging topic. For example, unmanned machines with navigation ability in unknown environments could perform tasks in many dangerous places that humans would not wish to entry for safety. Navigation in an unknown environment means no