Summary
Research into reactive collision avoidance for unmanned aerial vehicles has been conducted on unmanned terrestrial and mini aerial vehicles utilising active Doppler radar obstacle detection sensors. Flight tests conducted by flying a mini UAV at an obstacle have confirmed that a simple reactive collision avoidance algorithm enables aerial vehicles to autonomously avoid obstacles. This builds upon simulation work and results obtained using a terrestrial vehicle that had already confirmed that active sensors and a reactive collision avoidance algorithm are able to successfully find a collision free path through an obstacle field.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Barrows, G.: Mixed-Mode VLSI Optic Flow Sensors For Micro Air Vehicles. PhD thesis, University of Maryland, College Park (1999)
Zufferey, J.: Bio-Inspired Vision-Based Flying Robots. PhD thesis, Ecole Polytechnique Federale De Lausanne (2005)
McGee, T., Sengupta, R., Hedrick, K.: Obstacle detection for small autonomous aircraft using sky segmentation. In: Proceedings of the IEEE International Conference on Robotics and Automation (2005)
Lee, D., Beard, R., Merrel, P., Zhan, P.: See and avoidance behaviors for autonomous navigation. In: SPIE Opics East, Robotics Technologies and Architectures, Mobile Robot XVI, vol. 5609-05 (2004)
Griffiths, S., Saunders, J., Curtis, A., McLain, T., Beard, R.: Obstacle and terrain, avoidance for miniature aerial vehicles. In: IEEE Robotics and Automation Magazine (to appear)
Gresham, I., et al.: Ultra-wideband radar sensors for short-range vehicular applications. Transactions on Microwave Theory and Techniques 52, 2105–2122 (2004)
Fontana, R., Richley, E., Marzullo, A., Beard, L., Mulloy, R., Knight, E.: An ultra wideband radar for micro air vehicles air vehicle applications. In: IEEE Conference on Ultra Wideband Systems and Technologies (2002)
Lingelbach, F.: Path Planning using Probabilistic Cell Decomposition. PhD thesis (2005)
Pettersson, P.: Sampling-based Path Planning for an Autonomous Helicopter. PhD thesis, Linkoping Institute of Technology at Linkoping University (2006)
Sinopoli, B., Micheli, M., Donato, G., Koo, J.: Vision based navigation for an unmanned air vehicle. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1757–1765 (2001)
Frew, E., Langelaan, J., Joo, S.: Adaptive receding horizon control for vision based navigation of small unmanned aircraft. In: Proceedings of the 2006 American Control Conference (2006)
Woll, J.: Vorad collision warning radar, pp. 369–372 (1995)
Brigham, E.: The Fast Fourier Transform. Prentice-Hall Inc., Englewood Cliffs (1974)
Sarabandi, K., Park, M.: A radar cross-section model for power lines at millimeter-wave frequencies. IEEE Transactions on Antennas and Propagation 51, 2353–2360 (2003)
Yonemoto, N., Yamamotoa, K., Yamadaa, K., Yasuib, H., Tanakab, N., Migliaccioc, C., Dauvignacc, J., Pichotc, C.: Performance of obstacle detection and collision warning system for civil helicopters. Proc. SPIE 6226 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Viquerat, A., Blackhall, L., Reid, A., Sukkarieh, S., Brooker, G. (2008). Reactive Collision Avoidance for Unmanned Aerial Vehicles Using Doppler Radar. In: Laugier, C., Siegwart, R. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75404-6_23
Download citation
DOI: https://doi.org/10.1007/978-3-540-75404-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75403-9
Online ISBN: 978-3-540-75404-6
eBook Packages: EngineeringEngineering (R0)