Obstacle detection, tracking and avoidance for a teleoperated UAV

Marcin Odelga, Paolo Stegagno, Heinrich H. Bulthoff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

50 Citations (Scopus)

Abstract

In this paper, we present a collision-free indoor navigation algorithm for teleoperated multirotor Unmanned Aerial Vehicles (UAVs). Assuming an obstacle rich environment, the algorithm keeps track of detected obstacles in the local surroundings of the robot. The detection part of the algorithm is based on measurements from an RGB-D camera and a Bin-Occupancy filter capable of tracking an unspecified number of targets. We use the estimate of the robot's velocity to update the obstacles state when they leave the direct field of view of the sensor. The avoidance part of the algorithm is based on the Model Predictive Control approach. By predicting the possible future obstacles states, it filters the operator commands to prevent collisions. The method is validated on a platform equipped with its own computational unit, which makes it self-sufficient in terms of external CPUs.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Robotics and Automation, ICRA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2984-2990
Number of pages7
ISBN (Electronic)9781467380263
DOIs
Publication statusPublished - 2016 Jun 8
Event2016 IEEE International Conference on Robotics and Automation, ICRA 2016 - Stockholm, Sweden
Duration: 2016 May 162016 May 21

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2016-June
ISSN (Print)1050-4729

Other

Other2016 IEEE International Conference on Robotics and Automation, ICRA 2016
Country/TerritorySweden
CityStockholm
Period16/5/1616/5/21

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Obstacle detection, tracking and avoidance for a teleoperated UAV'. Together they form a unique fingerprint.

Cite this