Lifelong mapping in the wild: Novel strategies for ensuring map stability and accuracy over time evaluated on thousands of robots

Author:

Banerjee Nandan,Lisin Dimitri,Lenser Scott R.,Briggs Jimmy,Baravalle Rodrigo,Albanese Victoria,Chen Yao,Karimian Arman,Ramaswamy Tyagaraja,Pilotti Pablo,Alonso Martin Llofriu,Nardelli Lucio,Lane Veronica,Moser Renaud,Huttlin Andrea Okerholm,Shriver Justin,Fong Phil

Publisher

Elsevier BV

Subject

Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference54 articles.

1. iRobot says 20 percent of the world’s vacuums are now robots;Etherington,2016

2. A general framework for lifelong localization and mapping in changing environment;Zhao,2021

3. Lifelong mapping using adaptive local maps;Banerjee,2019

4. View management for lifelong visual maps;Banerjee,2019

5. Fast nonlinear approximation of pose graph node marginalization;Ta,2018

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