Abstract
This chapter consists of different approaches for advanced integrated path planning, navigation, guidance and tracking control of mobile service robots in structured environments. As first topic, an algorithm for robot path planning in known environments with aim to generate collision free path from starting to destination point, is considered. It is assumed that all obstacles are static. The path planning problem is solved using particle swarm optimization algorithm. The second topic deals with control problems, providing a method which enabled the mobile robot guidance along a given path. This problem can be divided into two problems: generating trajectory from given path and trajectory tracking. Solution of the first problem is provided using radial basis neural networks, while solution of the second problem is provided using mobile robot guidance controller based on algorithms of rocket homing. Proposed algorithms are pure pursuit and deviated pursuit navigation algorithms. Experimental and simulation results show the efficiency of the proposed approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Canny J (1988) The complexity of robot motion planning. MIT Press, Cambridge
Chen X, Li Y (2007) Neural network predictive control for mobile robot using PSO with controllable random exploration velocity. Int J Intell Control Syst 12(3):217–229
Ćosić A, Šušić M, Ribić A, Katić D (2011) An Approach for Mobile Robot Trajectory Generation and Tracking. In: Proceedings of the 55. ETRAN conference, Banja Vrućíca, Bosnia and Herzegovina
Dutta S (2010) Obstacle avoidance of mobile robot using PSO based neuro fuzzy technique. Int J Comput Sci Eng 2(2):301–304
Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, pp 1942–1948
Kunwar F, Sheridan PK, Benhabib B (2010) Predictive guidance-based navigation for mobile robots: a novel strategy for target interception. J Intell Robot Syst 59:367–398
Laumond J (1998) Robot motion planning and control. Springer, London
LaValle S (2006) Planning algorithms. Cambridge University, Cambridge
Li Y, Chen X (2005) Mobile robot navigation using particle swarm optimization and adaptive neural networks. In: Proceedings of ICNC, pp 628–631
Masehian E, Sedighizadeh D (2007) Classic and heuristic approaches in robot motion planning—a chronological review. World Acad Sci Eng Technol 29:101–106
Nasrollahy AZ, Javadi HHS (2009) Using particle swarm optimization for robot path planning in dynamic environments with moving obstacles and target. Third European Symposium on computer modeling and simulation, Athens, Greece, 60–65, 2009
Patrick HL, Seltzer SM, Warren ME (1981) Guidance laws for short-range tactical missiles. J Guidance Control Dyn 4(2):98–108
Raja P, Pugazhenthi S (2012) Optimal path planning of mobile robots: a review. Int J Phys Sci 7(9):1314–1320
Xiao J, Michalewicz Z, Zhang L, Trojanowski K (1997) Adaptive evolutionary planner/navigator for mobile robots”. IEEE Trans Evol Comput 1:18–28
Acknowledgments
This project is supported by Ministry of Science and Education of Republic Serbia under the grants TR-35003 and III-44008.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Katić, D., Ćosić, A., Šušić, M., Graovac, S. (2014). An Integrated Approach for Intelligent Path Planning and Control of Mobile Robot in Structured Environment. In: Pisla, D., Bleuler, H., Rodic, A., Vaida, C., Pisla, A. (eds) New Trends in Medical and Service Robots. Mechanisms and Machine Science, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-01592-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-01592-7_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01591-0
Online ISBN: 978-3-319-01592-7
eBook Packages: EngineeringEngineering (R0)