Abstract
Two main algorithms are presented to use an UAV for surveillance purposes. A very fast algorithm for the scan of an unknown area has been implemented and tested: it permits to scan a domain for the definition of layout, boundaries, obstacles… Once that the area has been acquired, a second algorithm is used to monitor the regions of interest in an efficient way. A neural network has been built in order to choose the shortest path to reach a determined point, giving the drone the possibility to avoid unexpected obstacles. Finally these two algorithms has been tested to verify their accuracy and speed.
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
References
Reitsma CL (2009) A novel approach to vibration isolation in small, unmanned aerial vehicles. Technologies for Practical Robot Applications, 2009, TePRA
Cola F, Resta F, Ripamonti F (2014) A negative derivative feedback design algorithm. Smart Mater Struct 23(8):art. no. 085008
Serra M, Resta F, Ripamonti F (2013) Dependent modal space control. Smart Mater Struct 22(10):art. no. 105004
Rysdyk R (2003) UAV path following for constant line-of-sight. In: 2nd AIAA “Unmanned Unlimited” system, technologies, and operations – Aerospace, San Diego, 15–18 Sept 2003
Lumelsky V, Stepanov A (1987) Path planning strategies for point mobile automation moving amidst unknown obstacles of arbitrary shape. Algorithmica 2:403–430
Neumann de Carvalho R, Vidal HA, Vieira P, Ribeiro MI (1997) Complete coverage path planning and guidance for cleaning robots. In: IEEE catalog number: 97TH8280 ISIE’97, Guimariies
Yang SX, Chaomin Luo (2004) A neural network approach to complete coverage path planning. IEEE Trans Syst Man Cybern Part B 34(1):718–725
Lin Lei Houjun Wang, Qinsong Wu (2006) Improved genetic algorithms based path planning of mobile robot under dynamic unknown environment. In: Proceedings of the 2006 IEEE international conference on mechatronics and automation, Luoyang, 25–28 Jun 2006
Meng Wang, Liu JNK (2005) Fuzzy logic based robot path planning in unknown environment. In: Proceedings of the fourth international conference on machine learning and cybernetics, Guangzhou, 18–21 Aug 2005
Rivals I, Canvas D, Peronnaz L, Dreyfus G (1994) Modeling and control of mobile robots and intelligent vehicles by neural networks. In: IEEE conference on intelligent vehicles, Paris, 24–28 Oct 1994
Glasius R, Komoda A, Gielen SCAM (1995) Neural network dynamics for path planning and obstacle avoidance. Neural Netw 8(1):125–133, Copyright © 1994 Elsevier Science Ltd
Djugash J, Hammer B Neural networks for obstacle avoidance. Informal Publication
Yang SX, Max Meng (2000) An efficient neural network approach to dynamic robot motion planning. Neural Netw 13:143–148
Yang SX, Max Meng (2003) Real-time collision-free motion planning of a mobile robot using a neural dynamics-based approach. Neural Netw 14(6):1541–1552
Willms AR, Yang SX (2008) Real-time robot path planning via a distance-propagating dynamic system with obstacle clearance. IEEE Trans Syst Man Cybern Part B 38(3):884–893
Hong Qu, Yang SX, Willms AR, Zhang Y (2009) Real-time robot path planning based on a modified pulse-coupled neural network model. IEEE Tran Neural Netw 20(11):1724
Cazzulani G, Moschini S, Resta F, Ripamonti F (2013) A diagnostic logic for preventing structural failure in concrete displacing booms. Autom Constr 35:499–506
Ambrosio P, Cazzulani G, Resta F, Ripamonti F (2014) An optimal vibration control logic for minimising fatigue damage in flexible structures. J Sound Vib 333(5):1269–1280
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 The Society for Experimental Mechanics, Inc.
About this paper
Cite this paper
Cheli, F., Ripamonti, F., Vendramelli, D. (2015). Design of UAV for Surveillance Purposes. In: Allemang, R. (eds) Special Topics in Structural Dynamics, Volume 6. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-15048-2_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-15048-2_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-15047-5
Online ISBN: 978-3-319-15048-2
eBook Packages: EngineeringEngineering (R0)