Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Collision Avoidance with Limited Field of View Sensing: A Velocity Obstacle Approach
 
conference paper

Collision Avoidance with Limited Field of View Sensing: A Velocity Obstacle Approach

Roelofsen, Steven Adriaan  
•
Gillet, Denis  
•
Martinoli, Alcherio  
2017
2017 IEEE International Conference on Robotics and Automation (ICRA)
IEEE International Conference on Robotics and Automation

Collision avoidance, in particular between robots, is an important component for autonomous robots. It is a necessary component in numerous applications such as human-robot interaction, automotive or unmanned aerial vehicles. While many collision avoidance algorithms take into account actuation constraints, only a few consider sensing limitations. In this paper, we present a reciprocal collision avoidance algorithm based on the velocity obstacle approach that guarantees collision-free maneuvers even when the robots are only capable to sense their environment within a limited Field Of View (FOV). We also present the challenges associated to sensors with limited FOV, show the conditions under which maneuvering can be safely done, and the modifications that a velocity obstacle approach requires to satisfy such conditions. We provide simulations and real robot experiments to validate our approach.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

ICRA_2017.pdf

Type

Preprint

Version

Submitted version (Preprint)

Access type

openaccess

Size

947.35 KB

Format

Adobe PDF

Checksum (MD5)

d936a635dcde906ce3aa565b3956f5b9

Loading...
Thumbnail Image
Name

ICRA17_1039_VI_fi.mp4

Access type

openaccess

Size

9.5 MB

Format

Video MP4

Checksum (MD5)

2e7554c237926c43593ea8f2abae11b0

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés