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Detection of doors using a genetic visual fuzzy system for mobile robots

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Abstract

Doors are common objects in indoor environments and their detection can be used in robotic tasks such as map-building, navigation and positioning. This work presents a new approach to door-detection in indoor environments using computer vision. Doors are found in gray-level images by detecting the borders of their architraves. A variation of the Hough Transform is used in order to extract the segments in the image after applying the Canny edge detector. Features like length, direction, or distance between segments are used by a fuzzy system to analyze whether the relationship between them reveals the existence of doors. The system has been designed to detect rectangular doors typical of many indoor environments by the use of expert knowledge. Besides, a tuning mechanism based on a genetic algorithm is proposed to improve the performance of the system according to the particularities of the environment in which it is going to be employed. A large database of images containing doors of our building, seen from different angles and distances, has been created to test the performance of the system before and after the tuning process. The system has shown the ability to detect rectangular doors under heavy perspective deformations and it is fast enough to be used for real-time applications in a mobile robot.

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Authors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, E.T.S. de Ingeniería Informática, University of Granada, 18071, Granada, Spain

    Rafael Muñoz-Salinas, Eugenio Aguirre & Miguel García-Silvente

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  1. Rafael Muñoz-Salinas
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  2. Eugenio Aguirre
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  3. Miguel García-Silvente
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Correspondence to Rafael Muñoz-Salinas.

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Rafael Muñoz Salinas was born in Córdoba, Spain, in 1979. He received his M.S. degree in Computer Sciences from the University of Granada, Spain, in 2005. He is currently a PhD candidate at the University of Granada and associate Proffesor at the University of Cordoba. His research interests include Autonomous Robots, Soft Computing and Human-Robot Interaction.

Dr. Eugenio Aguirre received his M.S. degree in Computer Science in 1997 and his Ph.D. in Computer Science in 2000, both from the University of Granada, Spain. His doctoral dissertation was in a Behaviour-based Architecture for Mobile Robot Navigation. He is Senior Lecturer in the Department of Computer Science and Artificial Intelligence at the University of Granada, where is a member of the Intelligent Systems research group. He has written more than 30 papers in journals, book chapters, and conferences. He is in the Program Committee of several conferences and he is reviewer of several international journals. His current main research interests are in the fields of: Autonomous Robots, Softcomputing and Human-Robot Interaction.

Dr. Miguel Garcia-Silvente received his M.S. degree in Computer Science in 1994 and his Ph.D. in Computer Science in 1996, both from the University of Granada, Spain. His doctoral dissertation was in a Representation of 1D and 2D Information Using the Scale Concept. Nowadays, he is Senior Lecturer in the Department of Computer Science and Artificial Intelligence at the University of Granada, where is a member of the Intelligent Systems research group. He has written more than 30 papers in journals, book chapters, and conferences. He is in the Program Committee of several conferences and he is reviewer of several international journals. His current main research interests are in the fields of: Computer Vision, Pattern Recognition, Soft-computing and Human-Robot Interaction.

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Muñoz-Salinas, R., Aguirre, E. & García-Silvente, M. Detection of doors using a genetic visual fuzzy system for mobile robots. Auton Robot 21, 123–141 (2006). https://doi.org/10.1007/s10514-006-7847-8

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