Visual Localization of Mobile Robot Using Artificial Markers

Babinec, Andrej; Jurišica, Ladislav; Hubinský, Peter; Duchoň, František

doi:10.1016/j.proeng.2014.12.091

Cited by 79 publications

(33 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…to represent objects [18] [19], and 3D matching with data from stereo cameras [20] and structured light [21]. In recent years, the augmented reality (AR) markers are widely used to obtain pose information [22] [23], which possess the advantages of easier recognition and higher precision [24].…”

Section: Visual Recognition and Trackingmentioning

confidence: 99%

Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process

Wang

Harada

Wan

2019

2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)

View full text Add to dashboard Cite

Complex and skillful motions in actual assembly process are challenging for the robot to generate with existing motion planning approaches, because some key poses during the human assembly can be too skillful for the robot to realize automatically. In order to deal with this problem, this paper develops a motion planning method using skillful motions from demonstration, which can be applied to complete robotic assembly process including complex and skillful motions. In order to demonstrate conveniently without redundant thirdparty devices, we attach augmented reality (AR) markers to the manipulated object to track and capture poses of the object during the human assembly process, which are employed as key poses to execute motion planning by the planner. Derivative of every key pose serves as criterion to determine the priority of use of key poses in order to accelerate the motion planning. The effectiveness of the presented method is verified through some numerical examples and actual robot experiments.

show abstract

Section: Visual Recognition and Trackingmentioning

confidence: 99%

Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process

Wang

Harada

Wan

2019

2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)

View full text Add to dashboard Cite

show abstract

“…Unlike the visual localization done using a single marker reported in [29], we have used ArUco markers map (AMM) for two purposes: one is for the identification of the kinematic parameters of each leg. The other is for the trajectory tracking of the robot.…”

Section: Setupmentioning

confidence: 99%

“…In this work, we have proposed the use of the monocular camera with the AruCo markers to demonstrate it for the identification of Tarantula. Unlike the visual localization which is done using a single marker reported in [29], we have used ArUco markers map (AMM) that resulted in the improved measurement accuracy. The measurement performance of this approach is compared using the standard industrial robot KUKA KR6 R900 robot (KUKA, Augsburg, Germany) [30].…”

Section: Introductionmentioning

confidence: 99%

Tarantula: Design, Modeling, and Kinematic Identification of a Quadruped Wheeled Robot

et al. 2018

View full text Add to dashboard Cite

This paper firstly presents the design and modeling of a quadruped wheeled robot named Tarantula. It has four legs each having four degrees of freedom with a proximal end attached to the trunk and the wheels for locomotion connected at the distal end. The two legs in the front and two at the back are actuated using two motors which are placed inside the trunk for simultaneous abduction or adduction. It is designed to manually reconfigure its topology as per the cross-sections of the drainage system. The bi-directional suspension system is designed using a single damper to prevent the trunk and inside components from shock. Formulation for kinematics of the wheels that is coupled with the kinematics of each leg is presented. We proposed the cost-effective method which is also an on-site approach to estimate the kinematic parameters and the effective trunk dimension after assembly of the quadruped robot using the monocular camera and ArUco markers instead of high-end devices like a laser tracker or coordinate measurement machine. The measurement technique is evaluated experimentally and the same set up was used for trajectory tracking of the Tarantula. The experimental method for the kinematic identification presented here can be easily extended to the other mobile robots with serial architecture designed legs.

show abstract

“…Fiducial tags, or fiducial markers, are used in computer vision (CV) applications for robot localization [1,2], mapping and localization of large environments [3][4][5], or for pose estimation in medical endoscopy [6]. Markers are also used for metric purposes, e.g., for calibration [7] and monitoring changes in distances and orientations in historic structures [8].…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Maximal Perturbation in Point Sets while Preserving the Order Type

Fraga

Hernández

2019

MCA

View full text Add to dashboard Cite

Recently a new kind of fiducial marker based on order type (OT) has been proposed. Using OT one can unequivocally identify a set of points through its triples of point orientation, and therefore, there is no need to use metric information. These proposed order type tags (OTTs) are invariant under a projective transformation which allows identification of them directly from a photograph. The magnitude of noise in the point positions that a set of points can support without changing its OT, is named the maximal perturbation (MP) value. This value represents the maximal displacement that any point in the set can have in any direction without changing the triplet’s orientation in the set. A higher value of the MP makes an OTT instance more robust to perturbations in the points positions. In this paper, we address the problem of how to improve the MP value for sets of points. We optimize “by hand” the MP for all the 16 subsets of points in the set of OTs composed of six points, and we also propose a general algorithm to optimize all the sets of OTs composed of six, seven, and eight points. Finally, we show several OTTs with improved MP values, and their use in an augmented reality application.

show abstract

Visual Localization of Mobile Robot Using Artificial Markers

Cited by 79 publications

References 4 publications

Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process

Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process

Tarantula: Design, Modeling, and Kinematic Identification of a Quadruped Wheeled Robot

Optimizing the Maximal Perturbation in Point Sets while Preserving the Order Type

Contact Info

Product

Resources

About