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Customizable Perturbation Synthesis for Robust SLAM Benchmarking (2402.08125v1)

Published 12 Feb 2024 in cs.RO, cs.AI, cs.CV, and cs.MM
Customizable Perturbation Synthesis for Robust SLAM Benchmarking

Abstract: Robustness is a crucial factor for the successful deployment of robots in unstructured environments, particularly in the domain of Simultaneous Localization and Mapping (SLAM). Simulation-based benchmarks have emerged as a highly scalable approach for robustness evaluation compared to real-world data collection. However, crafting a challenging and controllable noisy world with diverse perturbations remains relatively under-explored. To this end, we propose a novel, customizable pipeline for noisy data synthesis, aimed at assessing the resilience of multi-modal SLAM models against various perturbations. This pipeline incorporates customizable hardware setups, software components, and perturbed environments. In particular, we introduce comprehensive perturbation taxonomy along with a perturbation composition toolbox, allowing the transformation of clean simulations into challenging noisy environments. Utilizing the pipeline, we instantiate the Robust-SLAM benchmark, which includes diverse perturbation types, to evaluate the risk tolerance of existing advanced multi-modal SLAM models. Our extensive analysis uncovers the susceptibilities of existing SLAM models to real-world disturbance, despite their demonstrated accuracy in standard benchmarks. Our perturbation synthesis toolbox, SLAM robustness evaluation pipeline, and Robust-SLAM benchmark will be made publicly available at https://github.com/Xiaohao-Xu/SLAM-under-Perturbation/.

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An Examination of the Placeholder Document Structure in LaTeX

This brief document embodies a minimal LaTeX structure, often utilized as a foundational template for academic papers. It exhibits several core components aligned with established norms in academic publishing. The provided content constitutes the skeleton of a LaTeX document, specifically highlighting configuration aspects relevant to document preparation, rather than substantive research findings.

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The line \bibliographystyle{plainnat} specifies the citation style to be used, indicating a preference for the plainnat style associated with the natbib package. This style plainnat offers flexibility for citing in author-year format, facilitating a nuanced approach to bibliographic entry configuration.

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Authors (9)
  1. Xiaohao Xu (46 papers)
  2. Tianyi Zhang (262 papers)
  3. Sibo Wang (59 papers)
  4. Xiang Li (1002 papers)
  5. Yongqi Chen (8 papers)
  6. Ye Li (155 papers)
  7. Bhiksha Raj (180 papers)
  8. Matthew Johnson-Roberson (72 papers)
  9. Xiaonan Huang (32 papers)
Citations (8)
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