Learning Driven Coarse-to-Fine Articulated Robot Tracking

Christian Rauch, Vladimir Ivan, Timothy Hospedales, Jamie Shotton, Maurice Fallon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work we present an articulated tracking approach for robotic manipulators, which relies only on visual cues from colour and depth images to estimate the robot’s state when interacting with or being occluded by its environment. We hypothesise that articulated model fitting approaches can only achieve accurate tracking if subpixel-level accurate correspondences between observed and estimated state can be
established. Previous work in this area has exclusively relied on either discriminative depth information or colour edge correspondences as tracking objective and required initialisation from joint encoders. In this paper we propose a coarse-to-fine articulated state estimator, which relies only on visual cues from colour edges and learned depth keypoints, and which is initialised from a robot state distribution predicted from
a depth image. We evaluate our approach on four RGB-D sequences showing a KUKA LWR arm with a Schunk SDH2 hand interacting with its environment and demonstrate that this combined keypoint and edge tracking objective can estimate the palm position with an average error of 2.5cm without using any joint encoder sensing.
Original languageEnglish
Title of host publication2019 IEEE International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages6604-6610
Number of pages7
ISBN (Electronic)978-1-5386-6027-0
ISBN (Print)978-1-5386-8176-3
DOIs
Publication statusPublished - 12 Aug 2019
Event2019 IEEE International Conference on Robotics and Automation (ICRA) - Montreal, Canada
Duration: 20 May 201924 May 2019
https://www.icra2019.org/

Publication series

Name
PublisherInstitute of Electrical and Electronics Engineers
ISSN (Print)1050-4729
ISSN (Electronic)2577-087X

Conference

Conference2019 IEEE International Conference on Robotics and Automation (ICRA)
Abbreviated titleICRA 2019
Country/TerritoryCanada
CityMontreal
Period20/05/1924/05/19
Internet address

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