Abstract
Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possibilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detection, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.
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References
Alahi, A., Ortiz, R., Vandergheynst, P.: FREAK: Fast Retina Keypoint. In: Proc. Int. Conf. on Computer Vision and Pattern Recognition, pp. 510–517 (2012)
Astua, C., Barber, R., Crespo, J., Jardon, A.: Object detection techniques applied on mobile robot semantic navigation. Sensors 14(4), 6734–6757 (2014)
Butko, N., Zhang, L., Cottrell, G., Movellan, J.: Visual salience model for robot cameras. In: Proc. 2008 IEEE. Int. Conf. on Rob. and Automation, pp. 2398–2403 (2008)
Calonder, M., Lepetit, V., Ozuysal, M., Trzcinski, T., Strecha, C., Fua, P.: BRIEF: Computing a Local Binary Descriptor Very Fast. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(7), 1281–1298 (2012)
Dmitriy, Y., Postolsky, A., Grigoriy, P., Gennadievich, G.: Mobile robots navigation based on artificial landmarks with machine vision system. World Applied Sciences Journal, 1467–1472 (2013)
Farrajota, M., Rodrigues, J.M.F., du Buf, J.M.H.: Optical flow by multi-scale annotated keypoints: a biological approach. In: Proc. Int. Conf. on Bio-inspired Systems and Signal Processing (BIOSIGNALS 2011), Rome, Italy, pp. 307–315 (2011)
Hossain, M., Rashid, M., Bhuiyan, M., Ahmed, S., Akhtaruzzaman, M.: A qualitative approach to mobile robot navigation using RFID. In: IOP Conference Series: Materials Science and Engineering, vol. 53(1), p. 012064 (2013)
Biswas, J., Veloso, M.: Depth camera based indoor mobile robot localization and navigation. In: Proc. IEEE Int. Conf. on Robotics and Automation, pp. 1697–1702 (May 2012)
Leutenegger, S., Chli, M., Siegwart, R.Y.: BRISK: Binary robust invariant scalable keypoints. In: IEEE International Conference on Computer Vision, pp. 2548–2555 (2011)
Morton, R., Olson, E.: Robust sensor characterization via max-mixture models: GPS sensors. In: Proc. Int. Conf. Intelligent Robots and Systems, pp. 528–533 (2013)
Oliva, A., Torralba, A.: Building the gist of a scene: the role of global image features in recognition. Progress in Brain Res.: Visual Perception 155, 23–26 (2006)
Peng, S., Dong, W.: Robot navigation system with RFID and sensors. In: Int. Conf. on Computer Distributed Control and Intelligent Environmental Monitoring, pp. 610–612 (2012)
Pyo, Y., Hasegawa, T., Tsuji, T., Kurazume, R., Morooka, K.: Floor sensing system using laser reflectivity for localizing everyday objects and robot. Sensors 14(4), 7524–7540 (2014)
Rodrigues, J., du Buf, J.M.H.: Multi-scale keypoints in V1 and beyond: object segregation, scale selection, saliency maps and face detection. BioSystems 2, 75–90 (2006)
Rodrigues, J., du Buf, J.M.H.: A cortical framework for invariant object categorization and recognition. Cognitive Processing 10(3), 243–261 (2009)
Saleiro, M., Rodrigues, J.M.F., du Buf, J.M.H.: Minimalistic vision-based cognitive SLAM. In: Proc. 4th Int. Conf. on Agents and Artificial Intelligence, Special Session on Intelligent Robotics, pp. 614–623 (2012)
Tao, Z., Bonnifait, P., Frémont, V., Ibaez-Guzman, J.: Mapping and localization using GPS, lane markings and proprioceptive sensors. In: Proc. Int. Conf. Intelligent Robots and Systems, pp. 406–412 (2013)
Terzić, K., Rodrigues, J.M.F., du Buf, J.M.H.: Fast cortical keypoints for real-time object recognition. In: Int. Conf. Image Processing, pp. 3372–3376 (2013)
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Saleiro, M., Terzić, K., Lobato, D., Rodrigues, J.M.F., du Buf, J.M.H. (2014). Biologically Inspired Vision for Indoor Robot Navigation. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_52
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DOI: https://doi.org/10.1007/978-3-319-11755-3_52
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