Methods for Movement Trajectory Determination in Space

Eriks Klavins


Unmanned aerial vehicles have become more widely used for military, security, building inspection etc. Flight path and collision avoidance are the main research tasks for UAV control. This paper serves as background for a new method, which can be used for UAV onboard trajectory determination. Collecting UAV control methods and their advantages is possible to create one method that collects advantages of various control methods. Trajectory is established by using the image sensor and image processing methods. New method can be used to cancel out inertial navigation system errors like GPS does.


Flight trajectory; inertial navigation system; optical flow; unmanned aerial vehicle

Full Text:



M. Blösch, S. Weiss, D. Scaramuzza, and R. Siegwart, “Vision based MAV navigation in unknown and unstructured environments,” Proc. IEEE Int. Conf. Robot. Autom., pp. 21–28, 2010.

N. Michael, J. Fink, and V. Kumar, “Cooperative manipulation and transportation with aerial robots,” Auton. Robots, pp. 1–14, 2010.

J.-C. Zufferey, A. Beyeler, and D. Floreano, “Optic flow to control small {UAV}s,” Work. Vis. Guid. Syst. small Auton. Aer. Veh. (at {IROS}’2008), no. c, pp. 4–6, 2008.

J. W. Oliver, “An introduction to inertial navigation,” Arq. Neuropsiquiatr., vol. 67, no. 3B, pp. 961–2, 2009.

N. Anjum, “Camera Localization in Distributed Networks Using Trajectory Estimation,” J. Electr. Comput. Eng., vol. 2011, pp. 1–13, 2011.

N. Anjum and A. Cavallaro, “Automated Localization of a Camera Network,” IEEE Intell. Syst., vol. 27, no. 5, pp. 10–18, 2012.

C. Taylor, A. Rahimi, J. Bachrach, H. Shrobe, and A. Grue,“Simultaneous localization, calibration, and tracking in an ad hoc sensor network,” Proc. 5th Int. Conf. Inf. Process. Sens. networks, p. 33, 2006.

A. Chiuso, P. Favaro, H. Jin, and S. Soatto, “Structure from motion causally integrated over time,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 4, pp. 523–535, 2002.

S. S. Beauchemin and J. L. Barron, “The computation of optical flow,” ACM Comput. Surv., vol. 27, no. 3, pp. 433–466, 1995.

J. Suh, S. You, and S. Oh, “A cooperative localization algorithm for mobile sensor networks,” 2012 IEEE Int. Conf. Autom. Sci. Eng., pp. 1126–1131, 2012.

V. Grabe, H. H. Bulthoff, and P. Robuffo Giordano, “Robust optical-flow based self-motion estimation for a quadrotor UAV,” IEEE Int. Conf. Intell. Robot. Syst., pp. 2153–2159, 2012.

T. Krajník, M. Nitsche, S. Pedre, L. Přeučil, and M. E. Mejail, “A simple visual navigation system for an UAV,” Int. Multi-Conference Syst. Signals Devices, SSD 2012 - Summ. Proc., 2012.

S. R. Taichung, “An edge-based approach to improve optical flow algorithm,” Computer (Long. Beach. Calif)., pp. 45–51, 2010.

DOI: 10.7250/tcc.2015.008


  • There are currently no refbacks.