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Team KTH’s Picking Solution for the Amazon Picking Challenge 2016

Almeida, Diogo, 1991- (author)
KTH,Robotik, perception och lärande, RPL
Ambrus, Rares (author)
KTH,Datorseende och robotik, CVAP
Caccamo, Sergio (author)
KTH,Robotik, perception och lärande, RPL
show more...
Chen, Xi (author)
KTH,Robotik, perception och lärande, RPL
Cruciani, Silvia, 1991- (author)
Pinto Basto De Carvalho, Joao F (author)
KTH,Robotik, perception och lärande, RPL
Haustein, Joshua (author)
KTH,Robotik, perception och lärande, RPL
Marzinotto, Alejandro (author)
KTH,Datorseende och robotik, CVAP
Vina, Francisco, 1990- (author)
KTH
Karayiannidis, Yiannis, 1980- (author)
KTH,Robotik, perception och lärande, RPL
Ögren, Petter, 1974- (author)
KTH,Optimeringslära och systemteori
Jensfelt, Patric, 1972- (author)
KTH,Robotik, perception och lärande, RPL
Kragic, Danica, 1971- (author)
KTH,Robotik, perception och lärande, RPL
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 (creator_code:org_t)
2017
2017
English.
In: Warehouse Picking Automation Workshop 2017.
  • Conference paper (pop. science, debate, etc.)
Abstract Subject headings
Close  
  • In this work we summarize the solution developed by Team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition simulated a warehouse automation scenario and it was divided in two tasks: a picking task where a robot picks items from a shelf and places them in a tote and a stowing task which is the inverse task where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting from a high level overview of our system and later delving into details of our perception pipeline and our strategy for manipulation and grasping. The solution was implemented using a Baxter robot equipped with additional sensors.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)

Keyword

Computer Science
Datalogi

Publication and Content Type

pop (subject category)
kon (subject category)

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