Tiered-Resolution Volumetric Mapping for Real-Time Simultaneous Planning and Mapping on Natural Outdoor Environments

Abstract:Real-time volumetric mapping for a planning robot is dominated by the cost of integrating and storing information at the finest resolution, yet only a small fraction of any map ever lies on or near a path the planner actually considers. We exploit this with a tiered-resolution mapping mechanism that integrates LiDAR into a single map structure at two resolutions simultaneously: fine inside a corridor around the robot's current plan, and coarse everywhere else. As opposed to traditional navigation pipelines where path planning uses the mapping result and provides no feedback, we propose a feedback loop where planning also informs mapping to dynamically integrate information at different leaf resolutions. Across two real-world teleoperated datasets, replayed and scored offline against an independent full-resolution map, the tiered maps are 13-15x smaller and require 6-8x less integration CPU time than a uniform fine map, while producing paths at a similar cost per meter as the ones generated from fine resolution maps on both scenarios. A uniform coarse map reaches the same size savings but its path quality collapses (+210% cost per meter) on the harder scenario, because it over-discretizes terrain the robot must traverse. Tiering approximates the coarse map's cheapness without its failure mode.

Robotics (cs.RO)

arXiv:2610.20476 [cs.RO]

(or arXiv:2610.20476v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.20476 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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