A Dynamic Target Tracking of Car-Like Wheeled Robot in a Sensor-Network Environment via Fuzzy Decentralized Sliding-Mode Grey Prediction Control

2007 ◽  
Author(s):  
Chih-Lyang Hwang ◽  
Tsai-Hsiang Wang ◽  
Ching-Chang Wong
Keyword(s):  
Target Tracking ◽  
Sensor Network ◽  
Sliding Mode ◽  
Network Environment ◽  
Grey Prediction ◽  
Wheeled Robot ◽  
Dynamic Target ◽  
Prediction Control

Dynamic Target Tracking Based on Particle Filter in Actual Environment

2013 ◽  
Vol 683 ◽  
pp. 824-827
Author(s):  
Tian Ding Chen ◽  
Chao Lu ◽  
Jian Hu
Keyword(s):  
Kalman Filter ◽  
Particle Filter ◽  
Target Tracking ◽  
Monitoring System ◽  
Filter Method ◽  
Complex Scene ◽  
Actual Environment ◽  
Dynamic Target ◽  
Gaussian System ◽  
Non Gaussian

With the development of science and technology, target tracking was applied to many aspects of people's life, such as missile navigation, tanks localization, the plot monitoring system, robot field operation. Particle filter method dealing with the nonlinear and non-Gaussian system was widely used due to the complexity of the actual environment. This paper uses the resampling technology to reduce the particle degradation appeared in our test. Meanwhile, it compared particle filter with Kalman filter to observe their accuracy .The experiment results show that particle filter is more suitable for complex scene, so particle filter is more practical and feasible on target tracking.

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