Abstract
Probabilistic volumetric mapping (PVM) represents a 3D environmental map for an autonomous robotic navigational task. A popular implementation such as Octomap is widely used in the robotics community for such a purpose. The Octomap relies on an octree to represent a PVM and its main bottleneck lies in massive ray-shooting to determine the occupancy of the underlying volumetric voxel grids. In this paper, we propose GPU-based ray shooting to drastically improve the ray shooting performance in Octomap. Our main idea is based on the use of recent ray-tracing RTX GPU, mainly designed for real-time photo-realistic computer graphics and the accompanying graphics API, known as DXR. Our ray-shooting first maps leaf-level voxels in the given octree to a set of axis-aligned bounding boxes (AABBs) and employ massively parallel ray shooting on them using GPUs to find free and occupied voxels. These are fed back into the CPU to update the voxel occupancy and restructure the octree. In our experiments, we have observed more than three-orders-of-magnitude performance improvement in terms of ray shooting using ray-tracing RTX GPU over a state-of-the-art Octomap CPU implementation, where the benchmarking environments consist of more than 77K points and 25K∼34K voxel grids.
Original language | English |
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Title of host publication | 2021 IEEE International Conference on Robotics and Automation, ICRA 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 5440-5445 |
Number of pages | 6 |
ISBN (Electronic) | 9781728190778 |
DOIs | |
State | Published - 2021 |
Event | 2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China Duration: 30 May 2021 → 5 Jun 2021 |
Publication series
Name | Proceedings - IEEE International Conference on Robotics and Automation |
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Volume | 2021-May |
ISSN (Print) | 1050-4729 |
Conference
Conference | 2021 IEEE International Conference on Robotics and Automation, ICRA 2021 |
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Country/Territory | China |
City | Xi'an |
Period | 30/05/21 → 5/06/21 |
Bibliographical note
Funding Information:This project was supported in part by the ITRC/IITP program (IITP-2021-2020-0-01460) and the NRF (2017R1A2B3012701) in South Korea.
Publisher Copyright:
© 2021 IEEE