Monocular Visionbased Obstacle Detectionavoidance For Unmanned Aerial Vehicles

• doi: 10.1109/IVS.2016.7535370
• title: Monocular vision-based obstacle detection/avoidance for unmanned aerial vehicles
• publisher: IEEE
• isbn: 978-1-5090-1822-2
• issn:
• rank: 3037
• access_type: LOCKED
• content_type: Conferences
• abstract: Robust real-time obstacle detection/avoidance is a challenging problem especially for micro and small aerial vehicles due to the limited number of the on-board sensors due to the battery constraint and low payload. Usually lightweight sensors such as CMOS camera are the best choice comparing with laser or radar sensors. For real-time applications, most studies focus on using stereo cameras to reconstruct a 3D model of the obstacles or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the state of the approaching obstacles using single camera is proposed. During the flight, this method is able to detect the changes of the size area of the obstacles. First, the method detects the feature points of the obstacles, and then extracts the obstacles that has probability of getting close. In addition, by comparing the changes in the area ratios of the obstacle in the image sequence, the method can decide if it is obstacle or not. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV can take the action of avoidance.
• article_number: 7535370
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7535370
• html_url: https://ieeexplore.ieee.org/document/7535370/
• abstract_url: https://ieeexplore.ieee.org/document/7535370/
• publication_title: 2016 IEEE Intelligent Vehicles Symposium (IV)
• conference_location: Gothenburg, Sweden
• conference_dates: 19-22 June 2016
• publication_number: 7527552
• is_number: 7535353
• publication_year: 2016
• publication_date: 19-22 June 2016
• start_page: 92
• end_page: 97
• citing_paper_count: 35
• citing_patent_count: 0
• download_count: 2344
• insert_date: 20160808
• index_terms:
  • ieee_terms:
    • Feature extraction
    • Cameras
    • Three-dimensional displays
    • Sensors
    • Laser radar
    • Solid modeling
    • Navigation
  • dynamic_index_terms:
    • Aerial Vehicles
    • Unmanned Aerial Vehicles
    • Feature Points
    • Characteristic Points
    • Image Position
    • Micro Air Vehicles
    • Micro Aerial Vehicles
    • Indoor Environments
    • Object Of Interest
    • Feature Detection
    • Low Power Consumption
    • Convex Hull
    • Inertial Measurement Unit
    • Inertial Sensors
    • Optical Flow
    • Consecutive Frames
    • Obstacle Avoidance
    • Obstacle Detection
    • Extended Kalman Filter
    • Monocular Camera
    • Eristalis
    • Drone Flying
    • Types Of Obstacles
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5090-1822-2, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5090-1821-5, isbnType: New-2005
• authors:
  • Author Name: Abdulla Al-Kaff
    Affiliation: Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
    Author URL: https://ieeexplore.ieee.org/author/37085649704
    ID: 37085649704
    Order: 1
    Author Affiliations:
    • Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
  • Author Name: Qinggang Meng
    Affiliation: Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
    Author URL: https://ieeexplore.ieee.org/author/37087174412
    ID: 37087174412
    Order: 2
    Author Affiliations:
    • Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
  • Author Name: David Martín
    Affiliation: Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
    Author URL: https://ieeexplore.ieee.org/author/38252754600
    ID: 38252754600
    Order: 3
    Author Affiliations:
    • Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
  • Author Name: Arturo de la Escalera
    Affiliation: Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
    Author URL: https://ieeexplore.ieee.org/author/37378145900
    ID: 37378145900
    Order: 4
    Author Affiliations:
    • Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
  • Author Name: José María Armingol
    Affiliation: Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain
    Author URL: https://ieeexplore.ieee.org/author/37283413500
    ID: 37283413500
    Order: 5
    Author Affiliations:
    • Intelligent Systems Lab, University Carlos III of Madrid C/Butarque 15 Leganés, Madrid, Spain

Image Sensor

• sensor_type: CMOS
• resolution: not specified
• dynamic_range: not specified
• pixel_size: not specified
• dark_current: not specified

Optical Data

• focal_length: not specified
• aperture: not specified
• field_of_view: 62 degrees
• distortion: not specified

Performance Metrics

Applications & Benefits

• cell_imaging: not specified
• benefits: not specified

Supporting Organizations

• supported_by: Spanish Government, Comunidad de Madrid, DGT

Manuscript Details

• publication_date: 19-22 June 2016

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • frame_rate
  • noise

Processed JSON Filename

request_cefcc530-0478-4f2d-970d-3f84f53d62d5-monocular_visionbased_obstacle_detectionavoidance_for_unmanned_aerial_vehicles.json