4 research outputs found

    Artificial Intelligence in the Path Planning Optimization of Mobile Agent Navigation

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    AbstractMany difficult problem solving require computational intelligence. One of the major directions in artificial intelligence consists in the development of efficient computational intelligence algorithms, like: evolutionary algorithms, and neural networks. Systems, that operate in isolation or cooperate with each other, like mobile robots could use computational intelligence algorithms for different problems/tasks solving, however in their behavior could emerge an intelligence called system's intelligence, intelligence of a system. The traveling salesman problem TSP has a large application area. It is a well-known business problem. Maximum benefits TSP, price collecting TSP have a large number of economic applications. TSP is also used in the transport logic Raja, 2012. It also has a wide range of applicability in the mobile robotic agent path planning optimization. In this paper a mobile robotic agent's path planning will be discussed, using unsupervised neural networks for the TSP solving, and from the TSP results the finding of a closely optimal path between two points in the agent's working area. In the paper a modification of the criteria function of the winner neuron selection will also be presented. At the end of the paper measurement results will be presented

    Practical Application and Construction for Mobile Robot

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    This paper describes the construction of a rover mobile robot which is used to follow the resultant optimal path from the global path planning technique. A remote computer is used to control the motion of the mobile robot and to upload the data of the path wirelessly. The control (positioning and directing) of the robot is based on the readings of two wheel encoders. The current direction and position of the robot are calculated relatively to its previous direction and position. The control algorithm is capable to move the mobile robot in order to follow a certain path. The software of the control algorithm is executed using PIC microcontroller. To prove the efficiency of the control algorithm, this algorithm applied on the constructed mobile robot to move it in real world environment between different start and end points. The constructed mobile robot shows that it can follow the required path and reach the target within specified error percent

    A comparative study of smooth path planning for a mobile robot by evolutionary multi-objective optimization

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