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


T he high-speed civil transport (HSCT) aircraft has been designed with limited cockpit visibility. To handle this, the National Aeronautics and Space Administration (NASA) has proposed an external visibility system (XVS) to aid pilots in overcoming this lack of visibility. XVS obtains video images using high-resolution cameras mounted on and directed outside the aircraft. Images captured by the XVS enable automatic computer analysis in real-time, and thereby alert pilots about potential flight path hazards. Thus, the system is useful in helping pilots avoid air collisions. In this study, a system was configured to capture image sequences from an on-board high-resolution digital camera at a live video rate, record the images into a highspeed disk array through a fiber channel, and process the images using a Datacube MaxPCI machine with multiple pipelined processors to perform real-time obstacle detection. In this paper, we describe the design, implementation, and evaluation of this computer vision system. Using this system, real-time obstacle detection was performed and digital image data were obtained successfully in flight tests conducted at NASA Langley Research Center in January and September 1999. The system is described in detail so that other researchers can easily replicate the work.

DOI: 10.1006/rtim.2001.0272

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@article{Yang2002RealTimeIO, title={Real-Time Implementation of Obstacle Detection Algorithms on a Datacube MaxPCI Architecture}, author={Mau-Tsuen Yang and Tarak Gandhi and Rangachar Kasturi and Lee D. Coraor and Octavia I. Camps and Jeffrey McCandless}, journal={Real-Time Imaging}, year={2002}, volume={8}, pages={157-172} }