From Event: SPIE Optical Engineering + Applications, 2016
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.
Ulises Orozco-Rosas, Kenia Picos, Oscar Montiel, Roberto Sepúlveda, and Víctor H. Díaz-Ramírez, "Obstacle recognition for path planning in autonomous mobile robots," Proc. SPIE 9970, Optics and Photonics for Information Processing X, 99700X (Presented at SPIE Optical Engineering + Applications: August 30, 2016; Published: 14 September 2016); https://doi.org/10.1117/12.2237412.
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