High-Precision Visual-Tracking using the IMM Algorithm and Discrete GPI Observers (IMM-DGPIO): Categories (4)(7)

In this work, we propose the integration of a bank of Discrete Generalized Proportional Integral Observers (DGPIO) within an Interacting Multiple Model (IMM) structure in order to improve the precision of visual-tracking tasks. Applications such as visual servoing, robotic assisted surgery and optro...

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Bibliographic Details
Published in:Journal of intelligent & robotic systems 2020-09, Vol.99 (3-4), p.815-835
Main Authors: Sánchez-Ramírez, Edwards Ernesto, Rosales-Silva, Alberto Jorge, Alfaro-Flores, Rogelio Antonio
Format: Article
Language:English
Subjects:
Artificial Intelligence
Control
Electrical Engineering
Engineering
Mechanical Engineering
Mechatronics
Robotics
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Summary:In this work, we propose the integration of a bank of Discrete Generalized Proportional Integral Observers (DGPIO) within an Interacting Multiple Model (IMM) structure in order to improve the precision of visual-tracking tasks. Applications such as visual servoing, robotic assisted surgery and optronic weapon systems require accurate and high-precision measurements provided by real-time visual-tracking systems. In this case, the DGPIO-Bank was designed using two kinematic models based in constant velocity (CV) and constant acceleration (CA) motion profiles. The main feature of the DGPIO-Bank is the active disturbance rejection (ADR) feature which reduces noise in the position signal of a moving object. The resultant algorithm uses a fusion of four important features: state interaction, Kalman filtering, active disturbance rejection and multiple models combination. For performance comparison, we evaluated our proposed IMM-DGPIO algorithm and other state of the art IMM algorithms. Experimental results show that our proposed strategy had the best performance.
ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-020-01164-6