Frontier Detection and Reachability Analysis for Efficient 2D Graph-SLAM Based Active Exploration
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Abstract (arXiv)
We propose an integrated approach to active exploration by exploiting the Cartographer method as the base SLAM module for submap creation and performing efficient frontier detection in the geometrically co-aligned submaps induced by graph optimization. We also carry out analysis on the reachability of frontiers and their clusters to ensure that the detected frontier can be reached by robot. Our method is tested on a mobile robot in real indoor scene to demonstrate the effectiveness and efficiency of our approach.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Sep 2020.
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Citing papers per year: 2024: 2; 2025: 1.
3 papers.
- 2024Open-vocabulary Mobile Manipulation in Unseen Dynamic Environments with 3D Semantic Mapscited by 13
- 2024Multimodal LLM Guided Exploration and Active Mapping using Fisher Informationcited by 9
- 2025SD-OVON: A Semantics-aware Dataset and Benchmark Generation Pipeline for Open-Vocabulary Object Navigation in Dynamic Scenescited by 0
- 2025SD-OVON: A Semantics-aware Dataset and Benchmark Generation Pipeline for Open-Vocabulary Object Navigation in Dynamic Scenes24 May 2025
- 2024Multimodal LLM Guided Exploration and Active Mapping using Fisher Information22 Oct 2024
- 2024Open-vocabulary Mobile Manipulation in Unseen Dynamic Environments with 3D Semantic Maps26 Jun 2024