Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
38 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
41 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Robust SLAM Systems: Are We There Yet? (2109.13160v1)

Published 27 Sep 2021 in cs.RO

Abstract: Progress in the last decade has brought about significant improvements in the accuracy and speed of SLAM systems, broadening their mapping capabilities. Despite these advancements, long-term operation remains a major challenge, primarily due to the wide spectrum of perturbations robotic systems may encounter. Increasing the robustness of SLAM algorithms is an ongoing effort, however it usually addresses a specific perturbation. Generalisation of robustness across a large variety of challenging scenarios is not well-studied nor understood. This paper presents a systematic evaluation of the robustness of open-source state-of-the-art SLAM algorithms with respect to challenging conditions such as fast motion, non-uniform illumination, and dynamic scenes. The experiments are performed with perturbations present both independently of each other, as well as in combination in long-term deployment settings in unconstrained environments (lifelong operation).

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (6)
  1. Mihai Bujanca (3 papers)
  2. Xuesong Shi (11 papers)
  3. Matthew Spear (1 paper)
  4. Pengpeng Zhao (25 papers)
  5. Barry Lennox (9 papers)
  6. Mikel Lujan (31 papers)
Citations (32)