Jump to Content
  1. Oxford
  2. MPLS
  3. Eng. Sci.
  4. ORI

Estimation, Search, and Planning (ESP) Research Group

ESP @ ICRA 2018

Rowan Border presented the Surface Edge Explorer (SEE) next best view (NBV) algorithm at ICRA 2018 in Brisbane, Australia. You can read the paper on arXiv.

Authors
  1. R. Border
  2. J. D. Gammell
  3. P. Newman
Title
Surface Edge Explorer (SEE): Planning next best views directly from 3D observations
Publication
Conference
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)
Pages
1–8
Location
Brisbane, Australia
Date
Code
Code
Videos
Video
Presentations
Presentation
PDFs
PDF
Digital Object Identifier (DOI)
doi: 10.1109/ICRA.2018.8461098
Google Scholar
Google Scholar

Abstract

Surveying 3D scenes is a common task in robotics. Systems can do so autonomously by iteratively obtaining measurements. This process of planning observations to improve the model of a scene is called Next Best View (NBV) planning.

NBV planning approaches often use either volumetric (e.g., voxel grids) or surface (e.g., triangulated meshes) representations. Volumetric approaches generalise well between scenes as they do not depend on surface geometry but do not scale to high-resolution models of large scenes. Surface representations can obtain high-resolution models at any scale but often require tuning of unintuitive parameters or multiple survey stages.

This paper presents a scene-model-free NBV planning approach with a density representation. The Surface Edge Explorer (SEE) uses the density of current measurements to detect and explore observed surface boundaries. This approach is shown experimentally to provide better surface coverage in lower computation time than the evaluated state-of-the-art volumetric approaches while moving equivalent distances.