Vision-based autonomous landing of an unmanned aerial vehicle

By Srikanth Saripalli, James F. Montgomery, G. Sukhatme. Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002

322 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/125c250ffee24c829cfa548c8f7d0976293ad29a

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Vision-based control of a quadrotor for perching on lines (2014, methodology): “A relaxation of these assumptions using vision only for the detection of the target and its localization, but GPS for navigation in an absolute reference frame has been demonstrated for autonomous landing of helicopters outdoors [3].”
Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives (2016, methodology): “Using aerial imagery, the works [124]–[127] describe landing approach by the experiment and introduce a design and implementation of a real time vision-based algorithm.”
Vision based MAV navigation in unknown and unstructured environments (2010, methodology): “This has been implemented by Chen et al. [17] by constructing an Euclidean homography based on some feature points on the leading vehicle.”
PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision (2012, background): “Impressive results have been shown in terms of autonomous take-off, landing and navigation as well as obstacle avoidance (Conte and Doherty 2008; Saripalli et al. 2002; Johnson et al. 2005; Bosch et al. 2006; Scherer et al. 2008; Proctor et al. 2006; Kanade et al. 2004; Hrabar and Sukhatme 2009).”
Opportunities and challenges with autonomous micro aerial vehicles (2012, background): “though in open outdoor domains, this problem is seemingly solved with onboard GPS, IMU and camera sensors [45, 47], indoor domains and cluttered outdoor environments still pose a considerable challenge.”
Vision-based autonomous quadrotor landing on a moving platform (2017, background): “Nevertheless, solutions for detecting the target based on motion-capture systems [4], or other sensors (e.g., GPS [9]) are available in the literature.”
Advanced closed loop visual navigation for micro aerial vehicles (2014, methodology): “Localization and Mapping with Cameras: Early work with camerabased navigation, mainly with larger classical helicopter models, has been shown for instance by Chapuis et al. (1996) and Saripalli et al. (2002).”