Single Robot Localisation Approach for Indoor Robotic Systems through Integration of Odometry and Artificial Landmarks

Ņikitenko, Agris; Liekna, Aleksis; Ekmanis, Martins; Kuļikovskis, Guntis; Andersone, Ilze

doi:10.2478/acss-2013-0006

Cited by 8 publications

(2 citation statements)

References 11 publications

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“…The "Unmanned Delivery Vehicle" is dominated by GPS, with RGB-D cameras and flash mines Sensors such as inertial measurement unit (IMU) and inertial measurement unit (IMU) can be used as auxiliary sensors for positioning, which can quickly obtain the real-time and accurate position information of the robot outdoors, and basically solve the outdoor positioning problem [3][4]. Although GPS has played a great role in outdoor positioning, it is not suitable for indoor robot positioning due to the influence of buildings or walls.…”

Section: Introductionmentioning

confidence: 99%

Robot navigation based on multi-sensor fusion

Deng

2023

J. Phys.: Conf. Ser.

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Over the past years, with the rapid development of artificial intelligence technology, mobile robots have appeared in more and more fields. Different types of robots play different roles. Due to the complex indoor environment, there are still many technical problems to be solved for robots. Aiming at the shortcomings of single sensor, low mileage accuracy, and poor security in traditional mobile robot navigation systems, we propose a mobile robot autonomous navigation system based on multi-sensor perception. This system integrates mainstream synchronous positioning and mapping algorithms, path planning algorithms, and positioning algorithms, and uses multiple sensors to compensate each other to achieve the automatic navigation function of the mobile robot. In order to verify the reliability of the method, We have carried out multi angle analysis in the simulation environment, and the experimental results show that the proposed navigation system is reliable in operation, high in mileage accuracy, and good in robustness, which broadens the application scenario of mobile robots.

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Section: Introductionmentioning

confidence: 99%

Robot navigation based on multi-sensor fusion

Deng

2023

J. Phys.: Conf. Ser.

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“…Rusdinar et al 18 adopted a design of ceiling-attached landmarks which used a grid of circular dots to represent identity and direction. Nikitenko et al 19 presented a design of square landmarks which used glyphs to encode the identity.…”

Section: Introductionmentioning

confidence: 99%

Design and recognition of artificial landmarks for reliable indoor self-localization of mobile robots

Liu

2017

International Journal of Advanced Robotic Systems

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This article presents a self-localization scheme for indoor mobile robot navigation based on reliable design and recognition of artificial visual landmarks. Each landmark is patterned with a set of concentric circular rings in black and white, which reliably encodes the landmark's identity under environmental illumination. A mobile robot in navigation uses an onboard camera to capture landmarks in the environment. The landmarks in an image are detected and identified using a bilayer recognition algorithm: A global recognition process initially extracts candidate landmark regions across the whole image and tries to identify enough landmarks; if necessary, a local recognition process locally enhances those unidentified regions of interest influenced by illumination and incompleteness and reidentifies them. The recognized landmarks are used to estimate the position and orientation of the onboard camera in the environment, based on the geometric relationship between the image and environmental frames. The experiments carried out in a real indoor environment show high robustness of the proposed landmark design and recognition scheme to the illumination condition, which leads to reliable and accurate mobile robot localization.

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Reliable Multi-robot Map Merging of Inaccurate Maps

Andersone

Ņikitenko

2014

Advances in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection

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Single Robot Localisation Approach for Indoor Robotic Systems through Integration of Odometry and Artificial Landmarks

Cited by 8 publications

References 11 publications

Robot navigation based on multi-sensor fusion

Robot navigation based on multi-sensor fusion

Design and recognition of artificial landmarks for reliable indoor self-localization of mobile robots

Reliable Multi-robot Map Merging of Inaccurate Maps

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