Abstract
In this paper, an optimal path planning method is proposed for mobile robots to maximize the collected information from object regions in a 2D space with static and movable obstacles. Therein, the path planning problem is solved by improved genetic algorithm, which introduces the attractive operator and repulsive operator besides the conventional crossover and mutation operators. The initial population path is obtained by solving the traveling salesman problem with pattern search method. The proposed approach can generate the optimal trajectory planning while meeting nonholomic and dynamical constraints. And the robot could real-time change its moving path in the local areas based on the artificial obstacle repulsive force and object region attractive force. Simulation results verify the effectiveness of the proposed approach.
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Zhang, R., Liu, W., Zhang, X., Jiang, F., Chen, B. (2015). Path Planning of Nonholonomic Mobile Robot for Maximum Information Collection in Dynamic Environment. In: Kim, JH., Yang, W., Jo, J., Sincak, P., Myung, H. (eds) Robot Intelligence Technology and Applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham. https://doi.org/10.1007/978-3-319-16841-8_26
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DOI: https://doi.org/10.1007/978-3-319-16841-8_26
Publisher Name: Springer, Cham
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