scholarly journals Obstacle detection algorithms for rotorcraft navigation

2002 ◽  
Author(s):  
Nitin Pande ◽  
Ying Huang ◽  
Anand Narasimhamurthy ◽  
Octavia I. Camps ◽  
Rangachar Kasturi
Keyword(s):  
Obstacle Detection ◽  
Detection Algorithms

scholarly journals AN ALGORITHM FOR PEDESTRIAN DETECTION IN MULTISPECTRAL IMAGE SEQUENCES

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 73-77 ◽  
Author(s):  
V. V. Kniaz ◽  
V. V. Fedorenko
Keyword(s):  
Optical Flow ◽  
Pedestrian Detection ◽  
Obstacle Detection ◽  
Multispectral Image ◽  
Low Light ◽  
Detection Algorithms ◽  
Optical Flows ◽  
The Difference ◽  
Self Driving Cars

The growing interest for self-driving cars provides a demand for scene understanding and obstacle detection algorithms. One of the most challenging problems in this field is the problem of pedestrian detection. Main difficulties arise from a diverse appearances of pedestrians. Poor visibility conditions such as fog and low light conditions also significantly decrease the quality of pedestrian detection. This paper presents a new optical flow based algorithm BipedDetet that provides robust pedestrian detection on a single-borad computer. The algorithm is based on the idea of simplified Kalman filtering suitable for realization on modern single-board computers. To detect a pedestrian a synthetic optical flow of the scene without pedestrians is generated using slanted-plane model. The estimate of a real optical flow is generated using a multispectral image sequence. The difference of the synthetic optical flow and the real optical flow provides the optical flow induced by pedestrians. The final detection of pedestrians is done by the segmentation of the difference of optical flows. To evaluate the BipedDetect algorithm a multispectral dataset was collected using a mobile robot.

Real-Time Implementation of Obstacle Detection Algorithms on a Datacube MaxPCI Architecture

2002 ◽  
Vol 8 (2) ◽  
pp. 157-172 ◽  
Author(s):  
Mau-Tsuen Yang ◽  
Tarak Gandhi ◽  
Rangachar Kasturi ◽  
Lee Coraor ◽  
Octavia Camps ◽  
...  
Keyword(s):  
Real Time ◽  
Obstacle Detection ◽  
Detection Algorithms

Unmanned air vehicles for targeting tasks

2018 ◽  
Vol 233 (5) ◽  
pp. 1926-1934
Author(s):  
Chimpalthradi R Ashokkumar
Keyword(s):  
Unmanned Vehicles ◽  
Obstacle Detection ◽  
The Body ◽  
Wide Field ◽  
Detection Algorithms ◽  
Flight Operations ◽  
Air Vehicle ◽  
Wide Field Of View ◽  
Aerial Vehicle ◽  
Fixed Order

Unmanned aerial vehicle in surveillance and reconnaissance operations are well known with its flight operations confining to the lateral and longitudinal plane where the altitude is maintained constant. The objective in these operations is to have a wide field of view when camera is mounted underneath the aircraft. However, in obstacle detection algorithms as well as in weapon-target assignments by an unmanned combat air vehicle, the sensors such as cameras and radars are mounted along the X direction of the body fixed frame. The unmanned vehicles with such sensor locations are expected to offer obstacle-camera and weapon-target line-of-sight engagements. These operations by the unmanned vehicles are referred as targeting tasks. In this paper, a procedure to use unmanned vehicles as targeting systems in pitch plane is presented with respect to a fixed order controller at the inner loop. The remote pilot's inputs at the outer loop is disengaged and to mimic these inputs, various flight path angles are scheduled thus depicting autonomous characteristics. Illustrations to depict targeting tasks are provided.

Sign in / Sign up

Export Citation Format

Share Document