A Novel Machine Vision Approach Applied for Autonomous Robotics Navigation

Lins, Rômulo Gonçalves; Givigi, Sidney N.; Hung, Shao-Ming; Noureldin, Aboelmagd

doi:10.1109/smc.2015.334

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…From the perspective that positioning is achieved via comparing a reconstructed digital environment with a preinput map, vision-based localization can also be regarded as a special point cloud-based positioning, treating pixels as data points in the cloud. It is a rapidly developed field and various schemes have been proposed, such as positioning by recognizing landmarks [23][24][25] or detecting motion by comparing successive images [26]. Novel algorithms are mainly based on deep learning, enabling robots to construct a 3D map with only one camera [13].…”

Section: Related Workmentioning

confidence: 99%

UWB Base Station Cluster Localization for Unmanned Ground Vehicle Guidance

Ding

et al. 2021

Mathematical Problems in Engineering

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In this paper, we seek to provide unmanned ground vehicles with positioning service using ultrawideband (UWB) technology, a high-accuracy positioning approach. UWB is chosen for two distinct reasons. First, it does not rely on global navigation satellite systems like GPS, making it able to be applied indoors or in an environment where GPS signal is unstable. Second, it is immune to interference from other signals and accurate enough to guide unmanned ground vehicles moving precisely in a complex environment within a narrow road. In this paper, three UWB base stations are aggregated as a group in a 2D space for localization. A large number of tests are performed with a UWB base station cluster in order to validate its positioning performance. Based on the experiment results, we further develop a dynamic particle swarm optimization-based algorithm and a genetic algorithm to deploy multiple clusters of UWB base stations to cover an area of interest. The performance of the proposed algorithms has been tested through a series of simulations. Finally, experiments using unmanned ground vehicles are carried out to validate the localization performance. The results confirm that the robots can follow complex paths accurately with the proposed UWB-based positioning system.

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