The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Voxblox: Incremental 3D Euclidean Signed Distance Fields for on-board MAV planning
Open accessAbstract
Micro Aerial Vehicles (MAVs) that operate in unstructured, unexplored environments require fast and flexible local planning, which can replan when new parts of the map are explored. Trajectory optimization methods fulfill these needs, but require obstacle distance information, which can be given by Euclidean Signed Distance Fields (ESDFs). We propose a method to incrementally build ESDFs from Truncated Signed Distance Fields (TSDFs), a common implicit surface representation used in computer graphics and vision. TSDFs are fast to build and smooth out sensor noise over many observations, and are designed to produce surface meshes. We show that we can build TSDFs faster than Octomaps, and that it is more accurate to build ESDFs out of TSDFs than occupancy maps. Our complete system, called voxblox, is available as open source and runs in real-time on a single CPU core. We validate our approach on-board an MAV, by using our system with a trajectory optimization local planner, entirely on-board and in real-time.
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Cites
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Self-citationReal-time 3D reconstruction at scale using voxel hashing
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Vision-Based Navigation Techniques for Unmanned Aerial Vehicles: Review and Challenges
Arafat, M. Y., Alam, M. M., & Moh, S. (2023) · Drones · doi:10.3390/drones7020089 · Cited by 319
An Efficient Sampling-Based Method for Online Informative Path Planning in Unknown Environments
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Self-citationMaplab: An Open Framework for Research in Visual-Inertial Mapping and Localization
Schneider, T., Dymczyk, M., Fehr, M., Egger, K., Lynen, S., Gilitschenski, I., & Siegwart, R. (2018) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2800113 · Cited by 267
Self-citationHydra: A Real-time Spatial Perception System for 3D Scene Graph Construction and Optimization
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Metadata
- Authors
- Oleynikova, H., Taylor, Z., Fehr, M., Siegwart, R., & Nieto, J.
- Venue
- 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Publisher
- IEEE
- Published
- 2017-09
- Pages
- 1366-1373
- OpenAlex
- W2607968634
- Cited by
- 658
- References
- 18
- FWCI
- 41.33
- Type
- conference paper
- Language
- en
- Open access
- green
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- Oleynikova, H., Taylor, Z., Fehr, M., Siegwart, R., & Nieto, J. (2017). Voxblox: Incremental 3D Euclidean Signed Distance Fields for on-board MAV planning. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/iros.2017.8202315
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