@article{
 title = {Efficient next-best-scan planning for autonomous 3D surface reconstruction of unknown objects},
 type = {article},
 year = {2015},
 keywords = {3D modeling,Active vision,Laser scanning,Next-best-view planning},
 pages = {611-631},
 volume = {10},
 id = {11c69588-77c0-3164-aacc-5a7c880b22cc},
 created = {2021-02-09T17:05:46.769Z},
 file_attached = {false},
 profile_id = {ad172e55-c0e8-3aa4-8465-09fac4d5f5c8},
 group_id = {1ff583c0-be37-34fa-9c04-73c69437d354},
 last_modified = {2021-08-03T10:14:32.619Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kriegel2015},
 folder_uuids = {990ab628-0917-4e89-b071-24bf1f44fad6,5439d198-93d5-4603-a7ce-201d423f231e,4f36a0a5-b08a-4f70-b020-4daf83cb0507},
 private_publication = {false},
 abstract = {This work focuses on autonomous surface reconstruction of small-scale objects with a robot and a 3D sensor. The aim is a high-quality surface model allowing for robotic applications such as grasping and manipulation. Our approach comprises the generation of next-best-scan (NBS) candidates and selection criteria, error minimization between scan patches and termination criteria. NBS candidates are iteratively determined by a boundary detection and surface trend estimation of the acquired model. To account for both a fast and high-quality model acquisition, that candidate is selected as NBS, which maximizes a utility function that integrates an exploration and a mesh-quality component. The modeling and scan planning methods are evaluated on an industrial robot with a high-precision laser striper system. While performing the new laser scan, data are integrated on-the-fly into both, a triangle mesh and a probabilistic voxel space. The efficiency of the system in fast acquisition of high-quality 3D surface models is proven with different cultural heritage, household and industrial objects.},
 bibtype = {article},
 author = {Kriegel, Simon and Rink, Christian and Bodenmüller, Tim and Suppa, Michael},
 doi = {10.1007/s11554-013-0386-6},
 journal = {Journal of Real-Time Image Processing},
 number = {4}
}

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