Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

By Luis Pérez, Íñigo Rodríguez, Nuria Rodríguez, Rubén Usamentiaga, Daniel F. García. Italian National Conference on Sensors, 2016

307 citations recorded by the source corpus.

In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.

Subfields: Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/116e0bdfb596d5d5a4e2d85d1c37e130d383d6f4

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In Computer Vision and Pattern Recognition

In Industrial and Manufacturing Engineering

Citations in the corpus

Symbiotic human-robot collaborative assembly (2019, background): “Illustration of laser triangulation [197].”
A Survey on Information and Communication Technologies for Industry 4.0: State-of-the-Art, Taxonomies, Perspectives, and Challenges (2019, background): “Vision systems are already widely adopted in industry, mainly for inspection and quality control processes, and are increasingly used to improve the safety of workers [167].”