Outlier-Robust Estimation: Hardness, Minimally Tuned Algorithms, and Applications

Nonlinear estimation in robotics and vision is typically plagued with outliers due to wrong data association or incorrect detections from signal processing and machine learning methods. This article introduces two unifying formulations for outlier-robust estimation, generalized maximum consensus (&l...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on robotics Vol. 38; no. 1; pp. 281 - 301
Main Authors:	Antonante, Pasquale, Tzoumas, Vasileios, Yang, Heng, Carlone, Luca
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive algorithms Algorithms Approximation algorithms autonomous systems Combinatorial analysis computational complexity computer vision Estimation Formulations Inliers (landforms) Machine learning maximum likelihood estimation Measurement uncertainty Object recognition Optimization Outliers (statistics) Particle measurements Polynomials Probabilistic logic resilient perception Robotics robust estimation Robustness Signal processing Signal processing algorithms Simultaneous localization and mapping
ISSN:	1552-3098, 1941-0468
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!