http://www.cnr.it/ontology/cnr/individuo/prodotto/ID179913
Obstacle Avoidance Algorithm for Safe Human-Robot Cooperation in Small Medium Enterprise Scenario (Contributo in atti di convegno)
- Type
- Label
- Obstacle Avoidance Algorithm for Safe Human-Robot Cooperation in Small Medium Enterprise Scenario (Contributo in atti di convegno) (literal)
- Anno
- 2009-01-01T00:00:00+01:00 (literal)
- Alternative label
N. Pedrocchi; M. Malosio; L. Molinari Tosatti; G. Ziliani; (2009)
Obstacle Avoidance Algorithm for Safe Human-Robot Cooperation in Small Medium Enterprise Scenario
in 40th International Symposium on Robotics, Barcellona, 10-13 Marzo 2009
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- N. Pedrocchi; M. Malosio; L. Molinari Tosatti; G. Ziliani; (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- 40th Interantional Symposium on Robotics, Proceeding of (literal)
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- Scopus (literal)
- Google Scholar (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Titolo
- Obstacle Avoidance Algorithm for Safe Human-Robot Cooperation in Small Medium Enterprise Scenario (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-84-920933-8-0 (literal)
- Abstract
- Small Medium Enterprise (SME) scenario is quite different from common high-volume
robotic applications. Many different types of technological operations are done in the same space and
the working area of the robot should not be fenced in order to allow the operators to frequently access
to it. Therefore, the need of a motion planning strategy to \"real time\" collision avoidance is mandatory.
This work presents a new algorithm to avoid collisions between robots and human operators taking
into account the complexity of an industrial scenario. The replanning and control problem has been
split in two different modules: identification of safe evasive directions of motion suitable to avoid static
obstacles (i.e., known in the off-line programming phase) and an enhanced Artificial Potential Field
algorithm (APF) developed in order to impose the correct robot behavior to avoid dynamic obstacles
(like human operator whose position is not predictable). In this work we assume to track the position of
the human with suitable sensors. (literal)
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