The model for optimal design of robot vision systems based on kinematic error correction

Xu, Kanglin; Luger, George F.

doi:10.1016/j.imavis.2006.04.020

Cited by 2 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In these sensors, the accuracy is a function of their specifications and the type of features used to represent the environment. Other kinds of commonly used sensors in robotics are cameras, more specifically, monocular, stereo, or trinocular vision systems [ 7 – 12 ]. In these cases, the accuracy of the sensor is a function of the captured image resolution and the features used in the representation.…”

Section: Introductionmentioning

confidence: 99%

Curvature-Based Environment Description for Robot Navigation Using Laser Range Sensors

Vázquez-Martín

Núñez

Bandera

et al. 2009

Sensors

View full text Add to dashboard Cite

This work proposes a new feature detection and description approach for mobile robot navigation using 2D laser range sensors. The whole process consists of two main modules: a sensor data segmentation module and a feature detection and characterization module. The segmentation module is divided in two consecutive stages: First, the segmentation stage divides the laser scan into clusters of consecutive range readings using a distance-based criterion. Then, the second stage estimates the curvature function associated to each cluster and uses it to split it into a set of straight-line and curve segments. The curvature is calculated using a triangle-area representation where, contrary to previous approaches, the triangle side lengths at each range reading are adapted to the local variations of the laser scan, removing noise without missing relevant points. This representation remains unchanged in translation or rotation, and it is also robust against noise. Thus, it is able to provide the same segmentation results although the scene will be perceived from different viewpoints. Therefore, segmentation results are used to characterize the environment using line and curve segments, real and virtual corners and edges. Real scan data collected from different environments by using different platforms are used in the experiments in order to evaluate the proposed environment description algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%