MaskUKF: An Instance Segmentation Aided Unscented Kalman Filter for 6D Object Pose and Velocity Tracking

MaskUKF: An Instance Segmentation Aided Unscented Kalman Filter for 6D Object Pose and Velocity Tracking

Tracking the 6D pose and velocity of objects represents a fundamental requirement for modern robotics manipulation tasks. This paper proposes a 6D object pose tracking algorithm, called MaskUKF, that combines deep object segmentation networks and depth information with a serial Unscented Kalman Filt...

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Bibliographic Details
Main Authors: Nicola A. Piga, Fabrizio Bottarel, Claudio Fantacci, Giulia Vezzani, Ugo Pattacini, Lorenzo Natale
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Robotics and AI
Subjects:
6D object pose tracking
object velocity tracking
unscented Kalman filtering
deep learning-aided filtering
closed loop manipulation
humanoid robotics
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2021.594583/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2021.594583/full

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