Target tracking using a hierarchical grey-fuzzy motion decision-making method

Luo, Ren C.; Chen, Tse Min; Su, Kuo-Lan

doi:10.1109/3468.925657

Cited by 49 publications

(23 citation statements)

References 11 publications

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“…This method was applied to a military project by Kulkarni et al, and while it appeared to be potentially effective, prediction accuracy data was not presented. Ohlsson and Wohlin [24] used artifact-based proxies of project scope to augment existing within-project prediction and planning processes. They concluded that the approach has potential in making plans, and deviations from those plans, which are more visible, and that it can increase managers' confidence that predictions are of the right order.…”

Section: Related Workmentioning

confidence: 99%

“…GST has a distinct advantage over the techniques described before, i.e., it can enable the establishment of a prediction model using just a small amount of known data. In the context of data starvation, GST is known to be effective and has been widely applied to address real-world problems in the domains of energy management [20], mobile communication [21], instrument measurement [22], stock price analysis [23], and image processing [24], [25]. In addition, Song et al [26] used GST to address the whole-project effort prediction problem in software engineering.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrate the GM(1,1) and Verhulst Models to Predict Software Stage Effort

Wang

Song

MacDonell

et al. 2009

IEEE Trans. Syst., Man, Cybern. C

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrate the GM(1,1) and Verhulst Models to Predict Software Stage Effort

Wang

Song

MacDonell

et al. 2009

IEEE Trans. Syst., Man, Cybern. C

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“…Various fuzzy logic approaches for control and decision making are used ( [8]- [13]). In [14], a fuzzy logic controller is used to solve the problem of pursuit.…”

Section: Introductionmentioning

confidence: 99%

Line of sight robot navigation toward a moving goal

Belkhouche

Rastgoufard

2006

IEEE Trans. Syst., Man, Cybern. B

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Abstract-In this paper, we consider the problem of robot tracking and navigation toward a moving goal. The goal's maneuvers are not a priori known to the robot. Thus, off-line strategies are not effective. To model the robot and the goal, we use geometric rules combined with kinematics equations expressed in a polar representation. The intent of the strategy is to keep the robot between a reference point, called the observer, and the goal. We prove under certain assumptions that the robot navigating using this strategy reaches the moving goal successfully. In the presence of obstacles, the method is combined with an obstacle avoidance algorithm. The robot then moves in two modes, the navigation mode and the obstacle avoidance mode. Simulation of various scenarios highlights the efficiency of the method and provides an instructive comparison between the paths obtained for different reference points.Index Terms-Line of sight guidance law, relative kinematics equations, robotic navigation toward a moving goal, tracking.

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“…To overcome the drawbacks of MM-based algorithms, in this paper, we incorporate the grey prediction [30,31], which is a modelfree method and requires no a priori dynamic model of target, into the standard particle filter (SPF) for maneuvering target tracking. The proposed grey prediction based particle filter (GP-PF) has both the inherent advantages of model-based and model-free system, and thus can improve the maneuvering target tracking performance.…”

Section: Introductionmentioning

confidence: 99%

Grey Prediction Based Particle Filter for Maneuvering Target Tracking

Chen¹,

Shi²,

Hong³

et al. 2009

PIER

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Abstract-For maneuvering target tracking, we propose a novel grey prediction based particle filter (GP-PF), which incorporates the grey prediction algorithm into the standard particle filter (SPF). The basic idea of the GP-PF is that new particles are sampled by both the state transition prior and the grey prediction algorithm. Since the grey prediction algorithm is a kind of model-free method and is able to predict the system state based on historical measurements other than establishing a priori dynamic model, the GP-PF can significantly alleviate the sample degeneracy problem which is common in SPF, especially when it is used for maneuvering target tracking. Simulations are conducted in the context of two typical maneuvering motion scenarios and the results indicate that the overall performance of the proposed GP-PF is better than the SPF and the multiple model particle filter (MMPF) when the tracking accuracy, computational complexity and tracking lost probability are considered. The performance improvements can be attributed to that the GP-PF has both model-based and model-free features.

show abstract

Target tracking using a hierarchical grey-fuzzy motion decision-making method

Cited by 49 publications

References 11 publications

Integrate the GM(1,1) and Verhulst Models to Predict Software Stage Effort

Integrate the GM(1,1) and Verhulst Models to Predict Software Stage Effort

Line of sight robot navigation toward a moving goal

Grey Prediction Based Particle Filter for Maneuvering Target Tracking

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