Fast Landmark Tracking and Localization Algorithm for the Mobile Robot Self-Localization

Yoon, Kuk-Jin; Jang, Gijeong; Kim, Sung Hoon; Kweon, In-So

doi:10.1016/s1474-6670(17)34293-3

Cited by 11 publications

(7 citation statements)

References 13 publications

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“…Visual landmarks are being widely used to increase the localization accuracy and has high potential for docking systems [11][12][13][14][15][16]. For example QR-based landmarks have been used extensively because of their capability to store large amounts of information and their resistance against distortion and damage [13].…”

Section: Related Workmentioning

confidence: 99%

Path Planning for Automatic Recharging System for Steep-Slope Vineyard Robots

Santos

Mendes

et al. 2017

ROBOT 2017: Third Iberian Robotics Conference

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Abstract. Develop cost-effective ground robots for crop monitoring in steep slope vineyards is a complex challenge. The terrain presents harsh conditions for mobile robots and most of the time there is no one available to give support to the robots. So, a fully autonomous steep-slope robot requires a robust automatic recharging system. This work proposes a multilevel system that monitors a vineyard robot autonomy, to plan offline the trajectory to the nearest recharging point and dock the robot on that recharging point considering visual tags. The proposed system called VineRecharge was developed to be deployed into a cost-effective robot with low computational power. Besides, this paper benchmarks several visual tags and detectors and integrates the best one into the VineRecharge system.

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Section: Related Workmentioning

confidence: 99%

Path Planning for Automatic Recharging System for Steep-Slope Vineyard Robots

Santos

Mendes

et al. 2017

ROBOT 2017: Third Iberian Robotics Conference

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“…The aim of our work is to propose a landmark that can be detected in broader horizontal angle range and has smaller size at the same time. The novel design was inspired by QR code detection algorithm described in [3] and [8]. The last one introduces artificial striped landmark.…”

Section: Artificial Landmarksmentioning

confidence: 99%

Fast Artificial Landmark Detection for Indoor Mobile Robots

Kartashov

Huletski

Krinkin

2015

Annals of Computer Science and Information Systems

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Abstract-Nowadays the big challenge in simultaneous localization and mapping (SLAM) of mobile robots is the creation of efficient and robust algorithms. Significant Number of SLAM algorithms rely on unique features or or use artificial landmarks received from camera images. Feature points and landmarks extraction from images have two significant drawbacks: CPU consumption and weak robustness depending on environment conditions. In this paper we consider performance issues for landmark detection, introduce a new artificial landmark design and fast algorithm for detecting and tracking them in arbitrary images. Also we provide results of performance optimization for different hardware platforms.

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“…Histogram technique presents an interesting and popular alternative for both template representation and comparison. It is slightly invariant to translation, rotation, skew and scale [14] [18], and thus leads to great results for target tracking by particle filter [22]. A common way to represent a template by an histogram is based on the chromaticity space (eq 1) because it reduces the illumination change caused by the brightness variation.…”

Section: Histogram Representation and Matchingmentioning

confidence: 99%

Particle Filter Approach Adapted to Catadioptric Images for Target Tracking Application

Bazin¹,

Yoon²,

Kweon³

et al. 2009

Procedings of the British Machine Vision Conference 2009

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This paper addresses the problem of object tracking by particle filter in catadioptric images. Whereas a large literature exists for traditional images, only a very few methods have been developed for catadioptric vision. We present two techniques to correctly deal with the strong distortion inherent to catadioptric images. First, we propose generating and diffusing the particles in the equivalent sphere space rather than in the original 2D catadioptric image. It allows to handle the specific distance associated to the distorted image in a general framework. Second, we use an adapted neighborhood to perform template matching by histogram comparison. It permits to compare templates quickly while using an active neighborhood for space-variant windows. An additional important feature of our system is that no interpolation is performed: we directly work on the original catadioptric image. Experimental results demonstrated the validity of the proposed approach.

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Fast Landmark Tracking and Localization Algorithm for the Mobile Robot Self-Localization

Cited by 11 publications

References 13 publications

Path Planning for Automatic Recharging System for Steep-Slope Vineyard Robots

Path Planning for Automatic Recharging System for Steep-Slope Vineyard Robots

Fast Artificial Landmark Detection for Indoor Mobile Robots

Particle Filter Approach Adapted to Catadioptric Images for Target Tracking Application

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