On filtering and compressing lageos laser range data

1983 ◽  
Vol 57 (1-4) ◽  
pp. 121-130 ◽  
Author(s):  
E. G. Masters ◽  
A. Stolz ◽  
B. Hirsch
Keyword(s):  
Author(s):  
Christoph Weinrich ◽  
Tim Wengefeld ◽  
Michael Volkhardt ◽  
Andrea Scheidig ◽  
Horst-Michael Gross

2012 ◽  
Vol 09 (04) ◽  
pp. 1250025 ◽  
Author(s):  
POLYCHRONIS KONDAXAKIS ◽  
HARIS BALTZAKIS

In human–robot interaction developments, detection, tracking and identification of moving objects (DATMO) constitute an important problem. More specifically, in mobile robots this problem becomes harder and more computationally expensive as the environments become dynamic and more densely populated. The problem can be divided into a number of sub-problems, which include the compensation of the robot's motion, measurement clustering, feature extraction, data association, targets' trajectory estimation and finally, target classification. Here, a mobile robot uses 2D laser range data to identify and track moving targets. A Joint Probabilistic Data Association with Interacting Multiple Model (JPDA-IMM) tracking algorithm associates the available laser data to track and provide an estimated state vector of targets' position and velocity. Potential moving objects are initially learned in a supervised manner and later on are autonomously classified in real-time using a trained Fuzzy ART neural network classifier. The recognized targets are fed back to the tracker to further improve the track initiation process. The resulting technique introduces a computationally efficient approach to already existing target-tracking and identification research, which is especially suited for real time application scenarios.


2011 ◽  
Vol 35 (3) ◽  
pp. 719-725 ◽  
Author(s):  
Thijs van Lankveld ◽  
Marc van Kreveld ◽  
Remco Veltkamp

1999 ◽  
Vol 11 (1) ◽  
pp. 25-32 ◽  
Author(s):  
Yoshinobu Ando ◽  
◽  
Takashi Tsubouchi ◽  
Shin’ichi Yuta

The present authors developed a laser range sensor with an ultra-wide view angle and a navigation scheme for a mobile robot to move along a corridor. Although the range sensor uses orthodox triangulation in measurement, the detectable angle is extended to 260 degrees. This ultra-wide-angle sensor consists of 5 laser fan beam projectors and 3 CCD cameras. All fan beams from laser projectors are aligned in one plane parallel to the floor, and beam reflections on objects are detected by CCD cameras with super-wide-angle lenses. This paper presents schemes for obtaining range data with the sensor and for following along a corridor and some results on long corridor navigation.


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