Joint pose and principal curvature refinement using quadrics

Andrew Spek, Tom Drummond

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)


In this paper we present a novel joint approach for optimising surface curvature and pose alignment. We present two implementations of this joint optimisation strategy, including a fast implementation that uses two frames and an offline multi-frame approach. We demonstrate an order of magnitude improvement in simulation over state of the art dense relative point-to-plane Iterative Closest Point (ICP) pose alignment using our dense joint frame-to-frame approach and show comparable pose drift to dense point-to-plane ICP bundle adjustment using low-cost depth sensors. Additionally our improved joint quadric based approach can be used to more accurately estimate surface curvature on noisy point clouds than previous approaches.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Robotics and Automation (ICRA 2017)
EditorsHaoyong Yu, Zhidong Wang
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)9781509046331
ISBN (Print)9781509046338
Publication statusPublished - 21 Jul 2017
EventIEEE International Conference on Robotics and Automation 2017 - Sands Expo and Convention Centre, Singapore, Singapore
Duration: 29 May 20173 Jun 2017 (Proceedings)


ConferenceIEEE International Conference on Robotics and Automation 2017
Abbreviated titleICRA 2017
Internet address

Cite this