An air combat simulator in the virtual reality with the visual tracking system and force-feedback components

This work presents a new multi-plane air combat simulator based on the visual servo system. The scenario is an air combat of two fighters in virtual reality. The escaping one is simulated by a Stewart platform with a force-feedback joystick, overall controlled by a human operator. The chaser is realized as a visual servo system, as if the simulated air fighter was equipped with a military light-of-sight (LOS) to lock on to the mentioned escaping air fighter. Specifically, any arbitrary-shaped object that appears on a screen reflecting the virtual space of the escaping fighter can be automatically detected and located by the visual system in real-time so that the 2-DOF camera simulating LOS can be controlled due to visual servo to keep the target object centered in the camera image. By sensing the motion of the camera platform, the autopilot of the chasing fighter tries to follow the escaping one as closely as possible with an aim of shooting it down. The overall system is experimented in a virtual reality environment to validate the underlying research work. A promising application of this setup is to evolve into an entertainment facility or a military training platform.

[1]  Roberto Brunelli,et al.  MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES , 2001 .

[2]  Joachim Denzler,et al.  A two stage real-time object tracking system , 1994 .

[3]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[4]  Y. Bar-Shalom,et al.  Tracking in a cluttered environment with probabilistic data association , 1975, Autom..

[5]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[6]  S. Birchfield,et al.  An elliptical head tracker , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).

[7]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[8]  Eric Nettleton,et al.  Real time Multi-UAV Simulator , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[9]  Nicu Sebe,et al.  Improving visual matching , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[10]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[11]  Yi-Ping Hung,et al.  A Fast Block Matching Algorithm Based on the Winner-Update Rule , 2000 .

[12]  Stanley T. Birchfield,et al.  Elliptical head tracking using intensity gradients and color histograms , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[13]  Jenq-Neng Hwang,et al.  A fast minimal path active contour model , 2001, IEEE Trans. Image Process..