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arXiv · 2109.13160

Robust SLAM Systems: Are We There Yet?

Mihai Bujanca·Xuesong Shi·Matthew Spear·Pengpeng Zhao·Barry Lennox·Mikel Lujan
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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).

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Mihai Bujanca, Xuesong Shi, Matthew Spear, Pengpeng Zhao, Barry Lennox, Mikel Lujan. 2021-09-27. Robust SLAM Systems: Are We There Yet?. https://arxiv.org/abs/2109.13160

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