scholarly journals Design optimisation for optically tracked pointers

2017 ◽  
Vol 8 (1) ◽  
pp. 10
Author(s):  
Bert De Coninck ◽  
Jan Victor ◽  
Patrick De Baets ◽  
Stijn Herregodts ◽  
Matthias Verstraete

The use of mechanical pointers in optical tracking systems is needed to aid registration processes of unlocated rigid bodies. Error on the target point of a pointer can cause wrong positioning of vital objects and as such these errors have to be avoided. In this paper, the different errors that originate during this process are described, after which this error analysis is used for the optimisation of an improved pointer design. The final design contains six coplanar fiducials, favored by its robustness and low error. This configuration of fiducials is then analysed theoretically as well as practically to understand how it is performing. The error on tracking the target point of the pointer is found with simulation to be around 0.7 times the error of measuring one fiducial in space. However, practically this error is about equal to the fiducial tracking error, due to the non-normally distributed errors on each separate fiducial.

2000 ◽  
Vol 5 (2) ◽  
pp. 98-107 ◽  
Author(s):  
Rasool Khadem ◽  
Clement C. Yeh ◽  
Mohammad Sadeghi-Tehrani ◽  
Michael R. Bax ◽  
Jeremy A. Johnson ◽  
...  

1994 ◽  
Author(s):  
Gillian K. Groves ◽  
Kim M. Chacon ◽  
Kenneth E. Prager ◽  
Larisa Stephan

2016 ◽  
Vol 24 (2) ◽  
pp. 335-342
Author(s):  
彭树萍 PENG Shu-ping ◽  
李 博 LI Bo ◽  
姜润强 JIANG Run-qiang ◽  
陈长青 CHEN Chang-qing ◽  
于洪君 YU Hong-jun

2011 ◽  
Vol 383-390 ◽  
pp. 5972-5977
Author(s):  
Song Gao ◽  
Xiao Xia Xu ◽  
Qin Kun Xiao ◽  
Quan Pan

In order to improve the control performance of airborne EO tracking systems, we develop a proposed variable universe control algorithm based on fuzzy reasoning. The algorithm combines a new fuzzy control algorithm with classic PID control algorithm and greatly improves the dynamic performance of the airborne EO tracking systems. The simulation results indicate that the adaptive fuzzy controller can ensure the precision of the system with better adaptability and robustness.


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