Vision-based obstacle detection for rotorcraft flight

The ability of rotorcraft to fly at low altitude is hindered by the high pilot workload required to avoid obstacles. The development of automation tools that can detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles would significantly reduce pilot workload and increase safety. This article describes an obstacle detection approach based on feature tracking and recursive range estimation that takes into account the characteristics of rotorcraft flight. The merits and weaknesses of the approach are discussed using image sequences from the laboratory and from flight. © 1992 John Wiley & Sons, Inc.

[1]  Rama Chellappa,et al.  Passive ranging using a moving camera , 1992, J. Field Robotics.

[2]  Banavar Sridhar,et al.  Object segmentation for helicopter guidance , 1992, Defense, Security, and Sensing.

[3]  Banavar Sridhar,et al.  Integration of Motion and Stereo Sensors in Passive Ranging Systems , 1990, 1990 American Control Conference.

[4]  Banavar Sridhar,et al.  Analysis of image-based navigation system for rotorcraft low-altitude flight , 1992, IEEE Trans. Syst. Man Cybern..

[5]  Allen R. Hanson,et al.  Model extension and refinement using pose recovery techniques , 1992, J. Field Robotics.

[6]  Banavar Sridhar,et al.  KALMAN FILTER BASED RANGE ESTIMATION FOR AUTONOMOUS NAVIGATION USING IMAGING SENSORS , 1990 .

[7]  Banavar Sridhar,et al.  Kalman Filter Based Range Estimation for Autonomous Navigation using Imaging Sensors , 1989 .

[8]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[9]  Computer Staff.  Computer Society Election , 1990 .

[10]  Raymond E. Suorsa,et al.  Clustering methods for removing outliers from vision-based range estimates , 1992, Other Conferences.

[11]  William B. Thompson,et al.  Disparity Analysis of Images , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Phillip N. Smith,et al.  Flight Data Acquisition for Validation of Passive Ranging Algorithms for Obstacle Avoidance , 1992 .

[13]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[14]  Bir Bhanu.  Understanding scene dynamics , 1989 .

[15]  Bir Bhanu,et al.  Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation , 1992, J. Field Robotics.

[16]  Thomas S. Huang,et al.  Some Experiments on Estimating the 3-D Motion Parameters of a Rigid Body from Two Consecutive Image Frames , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  D. Petkovic.  The need for accuracy verification of machine vision algorithms and systems , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Banavar Sridhar,et al.  Validation of vision-based obstacle detection algorithms for low-altitude helicopter flight , 1991 .

[19]  B. Sridhar,et al.  Passive Navigation Using Image Irradiance Tracking , 1989 .