DocumentCode :
2117243
Title :
On-line gradient based surface discontinuity detection for outdoor scanning range sensors
Author :
Adams, Martin D.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Volume :
3
fYear :
2001
fDate :
2001
Firstpage :
1726
Abstract :
Research in field robotics often utilises scanning range sensors to aid autonomous navigation. The article addresses reliable feature extraction from continuously scanning range sensors operating outdoors. Contrary to other detection methods, an algorithm is presented which detects features on-line, as soon as the range to that feature has been sensed. A model is derived which makes predictions of range, before each new range sample is recorded. These are used to produce validation regions within which each new sample should lie, provided it belongs to the surface with the same smoothness characteristics as its range predecessors. The detection process model adapts its validation region according to the spatial gradient of the surface being sensed, and is implemented in extended Kalman filter (EKF) recursive form. Results are demonstrated with laser detection and ranging (ladar) sensor data recorded outdoors
Keywords :
Kalman filters; discrete time systems; feature extraction; laser ranging; mobile robots; nonlinear filters; optical radar; path planning; autonomous navigation; extended Kalman filter recursive form; feature extraction; field robotics; online gradient based surface discontinuity detection; outdoor scanning range sensors; smoothness characteristics; validation regions; Computer vision; Data mining; Feature extraction; Laser radar; Navigation; Radar detection; Robot sensing systems; Sea surface; Sensor phenomena and characterization; Sonar detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on
Conference_Location :
Maui, HI
Print_ISBN :
0-7803-6612-3
Type :
conf
DOI :
10.1109/IROS.2001.977227
Filename :
977227
Link To Document :
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