On the Application of RGB-D SLAM Systems for Practical Localization of Mobile Robots

Kostusiak, Aleksander; Nowicki, Michał; Skrzypczyński, Piotr

doi:10.14313/jamris_2-2017/17

Cited by 2 publications

(1 citation statement)

References 35 publications

(74 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In spite of their simplicity RGB-D VO algorithms are very useful in several areas of robotics. A VO system can be applied as a stand-alone localization method [20], used as a front-end in pose-based SLAM [5], exploited to pre-process RGB-D data in global localization [26], or combined with other methods of estimating the robot's pose [12].…”

Section: Introduc Onmentioning

confidence: 99%

On the Efficiency of Population-Based Optimization in Finding Best Parameters for RGB-D Visual Odometry

Kostusiak¹,

Skrzypczyński²

2019

JAMRIS

Self Cite

View full text Add to dashboard Cite

Visual odometry es mates the transforma ons between consecu ve frames of a video stream in order to recover the camera's trajectory. As this approach does not require to build a map of the observed environment, it is fast and simple to implement. In the last decade RGB-D cameras proliferated in robo cs, being also the sensors of choice for many prac cal visual odometry systems. Although RGB-D cameras provide readily available depth images, that greatly simplify the frame-to-frame transforma ons computa on, the number of numerical parameters that have to be set properly in a visual odometry system to obtain an accurate trajectory es mate remains high. Whereas se ng them by hand is certainly possible, it is a tedious try-and-error task. Therefore, in this ar cle we make an assessment of two popula on-based approaches to parameter op miza on, that are for long me applied in various areas of robo cs, as means to find best parameters of a simple RGB-D visual odometry system. The op miza on algorithms inves gated here are parcle swarm op miza on and an evolu onary algorithm variant. We focus on the op miza on methods themselves, rather than on the visual odometry algorithm, seeking an efficient procedure to find parameters that minimize the es mated trajectory errors. From the experimental results we draw conclusions as to both the efficiency of the op miza on methods, and the role of parcular parameters in the visual odometry system.

show abstract