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Geometric real-time modeling and scanning using distributed depth sensors

Klarén, Anton LU and Roxling, Valdemar LU (2016) In LU-CS-EX 2016-16 EDA920 20161
Department of Computer Science
Abstract
Technological breakthroughs have in recent years heavily increased the availability of different types of sensors and the amount of computational power, allowing for much more advanced robotic applications. By mounting multiple depth sensors on the robot and designing a fast and robust system with state-of-the-art algorithms we have made the robot aware of its surroundings. First, the surrounding is scanned into a static geometrical model. Then that model is used to detect and extract deviations in new scannings, for further analysis, to make suitable decisions on how the robot should act. We have demonstrated the system in a safety-critical setup for industrial robots, slowing down and stopping the robot when a human is too close. The... (More)
Technological breakthroughs have in recent years heavily increased the availability of different types of sensors and the amount of computational power, allowing for much more advanced robotic applications. By mounting multiple depth sensors on the robot and designing a fast and robust system with state-of-the-art algorithms we have made the robot aware of its surroundings. First, the surrounding is scanned into a static geometrical model. Then that model is used to detect and extract deviations in new scannings, for further analysis, to make suitable decisions on how the robot should act. We have demonstrated the system in a safety-critical setup for industrial robots, slowing down and stopping the robot when a human is too close. The system is designed for modularity, allowing for many other completely different applications, such as complex object tracking and motion planning. (Less)
Popular Abstract (Swedish)
Dagens industrirobotar är helt omedvetna om sin omgivning och utför oftast enkla förprogrammerade uppgifter. Med flera moderna kameror som fångar tredimensionella bilder monterade på olika delar av roboten så får den ögon. Dessa kan sedan användas för att hålla koll och förstå vad som händer i dess närhet.
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author
Klarén, Anton LU and Roxling, Valdemar LU
supervisor
organization
alternative title
Detection of deviations in the surroundings for robotic applications
course
EDA920 20161
year
type
H3 - Professional qualifications (4 Years - )
subject
keywords
Robotics, Computer vision, SLAM, Depth sensors, System design, Safety
publication/series
LU-CS-EX 2016-16
report number
LU-CS-EX 2016-16
ISSN
1650-2884
language
English
id
8879851
date added to LUP
2016-06-10 15:06:33
date last changed
2016-06-10 15:06:33
@misc{8879851,
  abstract     = {Technological breakthroughs have in recent years heavily increased the availability of different types of sensors and the amount of computational power, allowing for much more advanced robotic applications. By mounting multiple depth sensors on the robot and designing a fast and robust system with state-of-the-art algorithms we have made the robot aware of its surroundings. First, the surrounding is scanned into a static geometrical model. Then that model is used to detect and extract deviations in new scannings, for further analysis, to make suitable decisions on how the robot should act. We have demonstrated the system in a safety-critical setup for industrial robots, slowing down and stopping the robot when a human is too close. The system is designed for modularity, allowing for many other completely different applications, such as complex object tracking and motion planning.},
  author       = {Klarén, Anton and Roxling, Valdemar},
  issn         = {1650-2884},
  keyword      = {Robotics,Computer vision,SLAM,Depth sensors,System design,Safety},
  language     = {eng},
  note         = {Student Paper},
  series       = {LU-CS-EX 2016-16},
  title        = {Geometric real-time modeling and scanning using distributed depth sensors},
  year         = {2016},
}