English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A Self-Contained Teleoperated Quadrotor: On-Board State Estimation and Indoor Obstacle Avoidance

Odelga, M., Stegagno, P., Kochanek, N., & Bülthoff, H. (2018). A Self-Contained Teleoperated Quadrotor: On-Board State Estimation and Indoor Obstacle Avoidance. In IEEE International Conference on Robotics and Automation (ICRA 2018) (pp. 7840-7847). Piscataway, NJ, USA: IEEE.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/21.11116/0000-0001-7D4E-D Version Permalink: http://hdl.handle.net/21.11116/0000-0002-4755-F
Genre: Conference Paper

Files

show Files
hide Files
:
ICRA-2018-Odelga.pdf (Any fulltext), 2MB
Name:
ICRA-2018-Odelga.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show
hide
Description:
-

Creators

show
hide
 Creators:
Odelga, M1, 2, 3, Author              
Stegagno, P, Author              
Kochanek, N, Author              
Bülthoff, HH2, 3, 4, Author              
Affiliations:
1Project group: Autonomous Robotics & Human-Machine Systems, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528704              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
4Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528701              

Content

show
hide
Free keywords: -
 Abstract: Indoor operation of unmanned aerial vehicles (UAVs) poses many challenges due to the lack of GPS signal and cramped spaces. The presence of obstacles in an unfamiliar environment requires reliable state estimation and active algorithms to prevent collisions. In this paper, we present a teleoperated quadrotor UAV platform equipped with an on-board miniature computer and a minimal set of sensors for this task. The platform is capable of highly accurate state-estimation, tracking of desired velocity commanded by the user and ensuring collision-free navigation. The robot estimates its linear velocity through a Kalman filter integration of inertial and optical flow (OF) readings with corresponding distance measurements. An RGB-D camera serves the purpose of providing visual feedback to the operator and depth measurements to build a probabilistic, robo-centric obstacle model, allowing the robot to avoid collisions. The platform is thoroughly validated in experiments in an obstacle rich environment.

Details

show
hide
Language(s):
 Dates: 2018-09
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: BibTex Citekey: OdelgaSKB2018
DOI: 10.1109/ICRA.2018.8463185
 Degree: -

Event

show
hide
Title: IEEE International Conference on Robotics and Automation (ICRA 2018)
Place of Event: Brisbane, Australia
Start-/End Date: 2018-05-21 - 2018-05-25

Legal Case

show

Project information

show

Source 1

show
hide
Title: IEEE International Conference on Robotics and Automation (ICRA 2018)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 7840 - 7847 Identifier: ISBN: 978-1-5386-3081-5