M
Morten Rufus Blas
Researcher at Technical University of Denmark
Publications - 22
Citations - 1109
Morten Rufus Blas is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Mobile robot & Robot. The author has an hindex of 9, co-authored 22 publications receiving 1055 citations. Previous affiliations of Morten Rufus Blas include Raytheon Intelligence and Information Systems.
Papers
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Book ChapterDOI
CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching
TL;DR: A suite of scale-invariant center-surround detectors (CenSurE) that outperform the other detectors, yet have better computational characteristics than other scale-space detectors, and are capable of real-time implementation are introduced.
Journal IssueDOI
Mapping, navigation, and learning for off-road traversal
Kurt Konolige,Motilal Agrawal,Morten Rufus Blas,Robert C. Bolles,Brian P. Gerkey,Joan Sola,Aravind Sundaresan +6 more
TL;DR: The main components that comprise the system, including stereo processing, obstacle and free space interpretation, long-range perception, online terrain traversability learning, visual odometry, map registration, planning, and control are described.
Proceedings ArticleDOI
Fast color/texture segmentation for outdoor robots
TL;DR: A compact color and texture descriptor has been developed and used in a two-stage fast clustering framework using K-means to perform online segmentation of natural images and results of applying this descriptor for segmenting a synthetic image are presented.
Journal ArticleDOI
Mapping, navigation, and learning for off-road traversal: Konolige et al.: Mapping, Navigation, and Learning for Off-Road Traversal
Kurt Konolige,Motilal Agrawal,Morten Rufus Blas,Robert C. Bolles,Brian P. Gerkey,Joan Sola,Aravind Sundaresan +6 more
TL;DR: The main components that comprise the system, including stereo processing, obstacle and free space interpretation, long‐range perception, online terrain traversability learning, visual odometry, map registration, planning, and control are described.
Journal ArticleDOI
Traversable terrain classification for outdoor autonomous robots using single 2D laser scans
TL;DR: This paper introduces an algorithm for terrain classification that fuses seven distinctly different classifiers: raw height, roughness, step size, curvature, slope, width and invalid data that is used to extract road borders, traversable terrain and identify obstacles.