Robust Vision-based Obstacle Avoidance for Micro Aerial Vehicles in Dynamic Environments

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

7 Citations (Scopus)
8 Downloads (Pure)

Abstract

In this paper, we present an on-board vision-based approach for avoidance of moving obstacles in dynamic environments. Our approach relies on an efficient obstacle detection and tracking algorithm based on depth image pairs, which provides the estimated position, velocity and size of the obstacles. Robust collision avoidance is achieved by formulating a chance-constrained model predictive controller (CC-MPC) to ensure that the collision probability between the micro aerial vehicle (MAV) and each moving obstacle is below a specified threshold. The method takes into account MAV dynamics, state estimation and obstacle sensing uncertainties. The proposed approach is implemented on a quadrotor equipped with a stereo camera and is tested in a variety of environments, showing effective on-line collision avoidance of moving obstacles.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Robotics and Automation, ICRA 2020
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages2682-2688
ISBN (Electronic)978-1-7281-7395-5
DOIs
Publication statusPublished - 2020
Event2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France
Duration: 31 May 202031 Aug 2020

Conference

Conference2020 IEEE International Conference on Robotics and Automation, ICRA 2020
Country/TerritoryFrance
CityParis
Period31/05/2031/08/20

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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