14 September 2016 Obstacle recognition for path planning in autonomous mobile robots
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Abstract
Computer vision is an important task in robotics applications. This work proposes an approach for autonomous mobile robot navigation using the integration of the template-matching filters for obstacle detection and the evolutionary artificial potential field method for path planning. The recognition system employs a digital camera to sense the environment of a mobile robot. The captured scene is processed by a bank of space variant filters in order to find the obstacles and a feasible area for the robot navigation. The path planning employs evolutionary artificial potential fields to derive optimal potential field functions using evolutionary computation. Simulation results to validate the analysis and implementation are provided; they were specifically made to show the effectiveness and the efficiency of the proposal.
Conference Presentation
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Ulises Orozco-Rosas, Ulises Orozco-Rosas, Kenia Picos, Kenia Picos, Oscar Montiel, Oscar Montiel, Roberto Sepúlveda, Roberto Sepúlveda, Víctor H. Díaz-Ramírez, Víctor H. Díaz-Ramírez, "Obstacle recognition for path planning in autonomous mobile robots", Proc. SPIE 9970, Optics and Photonics for Information Processing X, 99700X (14 September 2016); doi: 10.1117/12.2237412; https://doi.org/10.1117/12.2237412
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