English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Probabilistic volumetric mapping (PVM) represents a 3D environmental map foran autonomous robotic navigational task. A popular implementation such asOctomap is widely used in the robotics community for such a purpose. TheOctomap relies on octree to represent a PVM and its main bottleneck lies inmassive ray-shooting to determine the occupancy of the underlying volumetricvoxel grids. In this paper, we propose GPU-based ray shooting to drasticallyimprove the ray shooting performance in Octomap. Our main idea is based on theuse of recent ray-tracing RTX GPU, mainly designed for real-timephoto-realistic computer graphics and the accompanying graphics API, known asDXR. Our ray-shooting first maps leaf-level voxels in the given octree to a setof axis-aligned bounding boxes (AABBs) and employ massively parallel rayshooting on them using GPUs to find free and occupied voxels. These are fedback into CPU to update the voxel occupancy and restructure the octree. In ourexperiments, we have observed more than three-orders-of-magnitude performanceimprovement in terms of ray shooting using ray-tracing RTX GPU over astate-of-the-art Octomap CPU implementation, where the benchmarkingenvironments consist of more than 77K points and 25K~34K voxel grids.

Accelerating Probabilistic Volumetric Mapping using Ray-Tracing Graphics Hardware