![]() ![]() We develop the user interface to help users filling out the positions of the mobile robot and the obstacles on the supervised computer, such the initial point of the mobile robot, the start point and the target point. The mobile robot searches the target point to locate the positions of unknown obstacles, and avoids these obstacles moving in the motion platform. We set the relative dangerous grade for variety obstacles. The complexity environment contains variety obstacles, such as road, tree, river, gravel, grass, highway and unknown obstacle. The article programs the shortest path searching problems of the mobile robot in the complexity unknown environment, and uses the mobile robot to present the movement scenario from the start point to the target point in a collision-free space. ![]() Mobile robots move on the platform according to the programmed motion paths from the start points to the target points and avoid the collision points. In the experimental results, we use simulation method to search the motion paths of the assigned chesses on the user interface, and implement the simulation results on the chessboard platform using mobile robots. The supervised computer controls mobile robots according to the programmed motion paths of the assigned chess moving on the platform via wireless RF interface. The user interface programs the motion paths that are the shortest displacement using enhance A* searching algorithm and solves the collision problem of the programmed motion paths for the assigned chesses to and reprogram the new motion paths using enhance A* searching algorithm, too. Users play the chess game using the mouse to obey the evaluation algorithm on the user interface. The article programs the shortest motion paths of the multiple mobile robots to be applied in the Chinese chess game, and presents the movement scenario of the chess using mobile robots on the grid based chessboard platform. In the experimental results, mobile robots can receive the pattern formation command from the supervised computer, and change the original pattern formation to the assigned pattern formation on the motion platform, and avoid other mobile robots on real-time. The supervised computer programs pattern formation exchange according to the image recognition results, and controls mobile robots moving on the motion platform via wireless RF interface. We have been developed some pattern formations according to game applications, such as hook pattern formation, T pattern formation, L pattern formation, rectangle pattern formation, sward pattern formation and so on, and develop the user interface of the multi-robot system to program motion paths for variety pattern formation exchange on the supervised computer. We use Otsu algorithm to recognize the variety 2D bar code to classify variety pattern, and control five mobile robots to execute formation exchange, and present the movement scenario on the motion platform. The system contains an image recognition system, a motion platform, some wireless RF modules and five mobile robots. The article develops multi-pattern formation exchange using A* searching algorithm, and programs the shortest motion paths for mobile robots. Mobile robots can receive the pattern formation command from the supervised computer, and change the original pattern formation to the assigned pattern formation on the motion platform, and avoid other mobile robots. In the experimental results, the supervised computer can decides the arm gesture using fusion algorithms. Players can use variety arms’ gesture to control the multiple mobile robots to executed pattern formation exchange. The mobile robot receives the command from the supervised compute, and transmits the status of environment to the supervised computer via wireless RF interface. We develop the user interface for variety pattern formation exchange according to the minimum displacement on the supervised computer. We have been developed some pattern formations applying in the war game, such as rectangle pattern formation, long snake pattern formation, L pattern formation, sword pattern formation, cone pattern formation and so on. We use the inertia module to be embedded in the two arms, and use mobile robots to present the movement scenario of pattern formation exchange on the grid based motion platform. ![]() The inertia module detects two arms’ gesture of the player. The article designs the multiple pattern formation controls of the multi-robot system according to two arms’ gesture of the player, and uses flood fill searching algorithm and A* searching algorithm to program the motion paths.
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