Abstract
This paper presents an efficient control structure of two mobile robots based-visual navigation methods in an indoor environment. The proposed navigators are based on decision systems employed the necessary values estimated by a Lukas-Kanade (LK) algorithm of optical flow (OF) approach. The robots control systems use the generated motion values in order to detect and estimate the positions of the nearest obstacles and objects around each mobile robot. The multi-robot system task is to navigate autonomously in their environment safely without collisions. Obstacles are identified and detected by the employed cameras of each robot based on video acquisition and image processing steps. The efficiency of the proposed approach is verified in simulation using Visual Reality Toolbox. Simulation results demonstrate that the visual based control system allows autonomous navigation without any collision with obstacles.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cuesta, F., Ollero, A.: Intelligent Mobile Robot Navigation. Springer-Verlag, Berlin Heidelberg (2005). https://doi.org/10.1007/b14079
Benn, W., Lauria, S.: Robot navigation control based on monocular images: an image processing algorithm for obstacle avoidance decisions. Math. Probl. Eng. 1–14 (2012)
Cherroun, L., Nadour, M., Boudiaf, M., Kouzou, A.: Comparison between type-1 and type-2 Takagi-Sugeno fuzzy logic controllers for robot design. Electrotehnică Electronică Automatică 66(2), 94–103 (2018)
Aslani, S., Mahdavi-Nasab, H.: Optical flow based moving object detection and tracking for traffic surveillance. Int. J. Electr. Comput. Energ. Electron. Commun. Eng. 7(9), 1252–1256 (2013)
Guzel, M.S., Bicker, R.: Vision based obstacle avoidance techniques. Recent Adv. Mob. Robot. (InTech), 83–108 (2011). https://doi.org/10.5772/25540
Desouza, G.N., Kak, A.C.: Vision for mobile robot navigation. A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 24(2), 237 (2002)
Font, F.B., Ortiz, A., Oliver, G.: Visual navigation for mobile robots: a survey. J. Intel Robot Syst. 53, 263–296 (2008)
Gupta, M., Uggirala, B., Behera, L.: Visual navigation of a mobile robot in a cluttered environment. In: 17th World Congress of IFAC, Seoul, Korea (2008)
Tajti, F., et al.: Optical flow based odometry for mobile robots supported by multiple sensors and sensor fusion. Automatica 57(1), 201–211 (2016)
Singh, P., Tiwari, R., Bhattacharya, M.: Navigation in multi robot system using cooperative learning: a survey. In: 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT). IEEE (2016)
Corso, J.: Motion and Optical Flow. College of Engineering, in University of Michigan (2014)
Chao, H., Gu, Y., Napolitano, M.: A survey of optical flow techniques for robotics navigation applications. J. Intell. Robot. Syst. 73, 361–372 (2014). https://doi.org/10.1007/s10846-013-9923-6
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision (1981)
Tasalatsanis, A., Valavanis, K., Yalcin, Y.: Vision based target and collision avoidance for mobile robots. J. Intell. Robot. Syst. 48(2), 285–304 (2007). https://doi.org/10.1007/s10846-006-9096-7
Wang, C., Liu, W., Meng, M.Q.H.: Obstacle avoidance for quadrotor using improved method based on optical flow. In: IEEE International Conference on Information an Automation, pp. 1674–1679, Lijiang, China (2015)
Nadour, Mohamed, Boumehraz, Mohamed, Cherroun, Lakhmissi, Puig, Vicenç: Mobile robot visual navigation based on fuzzy logic and optical flow approaches. Int. J. Syst. Assur. Eng. Manage. 10, 1654–1667 (2019). https://doi.org/10.1007/s13198-019-00918-2
Nadour, M., Boumehraz, M., Cherroun, L., Puig, V.: Hybrid type-2 fuzzy logic obstacle avoidance system based on Horn-Schunck method. Electrotehnică, Electronică. Automatică (EEA) 67(3), 45–51 (2019)
Rocha, R., Dias, J., Carvalho, A.: Cooperative multi-robot systems a study of vision-based 3-D mapping using information theory. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pp. 384–389 (2005). https://doi.org/10.1109/ROBOT.2005.1570149
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Elasri, A., Cherroun, L., Nadour, M. (2022). Multi-robot Visual Navigation Structure Based on Lukas-Kanade Algorithm. In: Lejdel, B., Clementini, E., Alarabi, L. (eds) Artificial Intelligence and Its Applications. AIAP 2021. Lecture Notes in Networks and Systems, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-96311-8_50
Download citation
DOI: https://doi.org/10.1007/978-3-030-96311-8_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96310-1
Online ISBN: 978-3-030-96311-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)