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Feature optimization for long-range visual homing in changing environments.

Zhu Q, Liu X, Cai C - Sensors (Basel) (2014)

Bottom Line: In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments.To verify the feasibility of the proposal, several comprehensive evaluations are conducted.The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

View Article: PubMed Central - PubMed

Affiliation: College of Automation, Harbin Engineering University, Harbin 150001, China. zhuqidan@hrbeu.edu.cn.

ABSTRACT
This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

No MeSH data available.


The mobile robotic platform.
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f3-sensors-14-03342: The mobile robotic platform.

Mentions: Our experiments were performed with a crawler mobile robot (see Figure 3). A panoramic vision system, composed of a mirror with a diameter of 100 mm and a camera with a resolution of 800 × 800, was mounted on top of the robot. A 2 GHz Pentium (R) processor was dedicated to vision processing and robot control. In addition, the robot was equipped with a digital compass to acquire the global orientation.


Feature optimization for long-range visual homing in changing environments.

Zhu Q, Liu X, Cai C - Sensors (Basel) (2014)

The mobile robotic platform.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3958223&req=5

f3-sensors-14-03342: The mobile robotic platform.
Mentions: Our experiments were performed with a crawler mobile robot (see Figure 3). A panoramic vision system, composed of a mirror with a diameter of 100 mm and a camera with a resolution of 800 × 800, was mounted on top of the robot. A 2 GHz Pentium (R) processor was dedicated to vision processing and robot control. In addition, the robot was equipped with a digital compass to acquire the global orientation.

Bottom Line: In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments.To verify the feasibility of the proposal, several comprehensive evaluations are conducted.The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

View Article: PubMed Central - PubMed

Affiliation: College of Automation, Harbin Engineering University, Harbin 150001, China. zhuqidan@hrbeu.edu.cn.

ABSTRACT
This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

No MeSH data available.