FAR Planner: Fast, Attemptable Route Planner using Dynamic Visibility Update
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Abstract (arXiv)
The problem of path planning in unknown environments remains a challenging problem - as the environment is gradually observed during the navigation, the underlying planner has to update the environment representation and replan, promptly and constantly, to account for the new observations. In this paper, we present a visibility graph-based planning framework capable of dealing with navigation tasks in both known and unknown environments. The planner employs a polygonal representation of the environment and constructs the representation by extracting edge points around obstacles to form enclosed polygons. With that, the method dynamically updates a global visibility graph using a two-layered data structure, expanding the visibility edges along with the navigation and removing edges that become occluded by newly observed obstacles. When navigating in unknown environments, the method is attemptable in discovering a way to the goal by picking up the environment layout on the fly, updating the visibility graph, and fast re-planning corresponding to the newly observed environment. We evaluate the method in simulated and real-world settings. The method shows the capability to attempt and navigate through unknown environments, reducing the travel time by up to 12-47% from search-based methods: A*, D* Lite, and more than 24-35% than sampling-based methods: RRT*, BIT*, and SPARS.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Oct 2021.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 4; 2026: 1.
8 papers.
- 2025VL-Nav: Neuro-Symbolic Reasoning-based Vision-Language Navigationcited by 4
- 2024Real-Time Metric-Semantic Mapping for Autonomous Navigation in Outdoor Environmentscited by 2
- 2025CTSAC: Curriculum-Based Transformer Soft Actor-Critic for Goal-Oriented Robot Explorationcited by 1
- 2025Sight Over Site: Perception-Aware Reinforcement Learning for Efficient Robotic Inspectioncited by 1
- 2026DreamFlow: Local Navigation Beyond Observation via Conditional Flow Matching in the Latent Spacecited by 1
- 2023DEUX: Active Exploration for Learning Unsupervised Depth Perceptioncited by 0
- 2024An Earth Rover dataset recorded at the ICRA@40 partycited by 0
- 2025Towards Perception-based Collision Avoidance for UAVs when Guiding the Visually Impairedcited by 0
- 2026DreamFlow: Local Navigation Beyond Observation via Conditional Flow Matching in the Latent Space3 Mar 2026
- 2025Sight Over Site: Perception-Aware Reinforcement Learning for Efficient Robotic Inspection22 Sep 2025
- 2025Towards Perception-based Collision Avoidance for UAVs when Guiding the Visually Impaired17 Jun 2025
- 2025CTSAC: Curriculum-Based Transformer Soft Actor-Critic for Goal-Oriented Robot Exploration18 Mar 2025
- 2025VL-Nav: Neuro-Symbolic Reasoning-based Vision-Language Navigation2 Feb 2025
- 2024Real-Time Metric-Semantic Mapping for Autonomous Navigation in Outdoor Environments30 Nov 2024
- 2024An Earth Rover dataset recorded at the ICRA@40 party8 Jul 2024
- 2023DEUX: Active Exploration for Learning Unsupervised Depth Perception16 Sep 2023