One step back, two steps forward: learning moves to recover from SLAM tracking failures-Reference-Cited by-同舟云学术

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One step back, two steps forward: learning moves to recover from SLAM tracking failures

Published:2024-02-28 Issue:5 Volume:38 Page:307-322
ISSN:0169-1864
Container-title:Advanced Robotics
language:en
Short-container-title:Advanced Robotics

Author:

Hussain Qureshi Ans¹,Latif Anjum Muhammmad²,Hussain Wajahat²,Muddassar Usama²,Abbasi Sohail²

Affiliation:

1. Centre for Automation and Robotic Engineering Science (CARES), The University of Auckland, Auckland, New Zealand

2. Robotics & Machine Intelligence (ROMI) Lab, School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan

Funder

Higher Education Commission (HEC), Govt. of Pakistan

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01691864.2024.2319144

Reference49 articles.

1. Towards lifelong visual maps

2. Predicting Failures of Vision Systems

3. Introspective classification for robot perception

4. Deep introspective SLAM: deep reinforcement learning based approach to avoid tracking failure in visual SLAM

5. Saxena DM Kurtz V Hebert M. Learning robust failure response for autonomous vision based flight. In: ICRA; IEEE; 2017. p. 5824–5829.

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