Adaptive Path Planning for a Vision-Based quadrotor in an Obstacle Field: Beijing, China

Jaime Junell, Erik-Jan van Kampen

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

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Abstract

This paper demonstrates a real life approach for quadrotor obstacle avoidance in indoor flight. A color-based vision approach for obstacle detection is used to good effect conjointly with an adaptive path planning algorithm. The presented task is to move about a set indoor space while avoiding randomly located obstacles and adapting a path to prevent future confrontation with the obstacles all together. The goal is to complete this task with a solution that is simple and efficient. The result is an adaptive path planning algorithm that evades obstacles when necessary and uses these interactions to find an obstaclefree path with simple logic. The whole task is implemented within Paparazzi, an open source autopilot software. Flight tests are performed in an indoor flight arena with simulated GPS from a camera tracking system. Through these flight tests, the approach proves to be reliable and efficient
Original languageEnglish
Title of host publicationInternational Micro Air Vechicle Competition and Conference 2016
Subtitle of host publicationBe
Number of pages8
Publication statusPublished - 2016
EventInternational Micro Air Vechicle Competition and Conference 2016 - Beijing, China
Duration: 17 Oct 201621 Oct 2016
http://www.imavs.org/2016/

Conference

ConferenceInternational Micro Air Vechicle Competition and Conference 2016
Abbreviated titleIMAV2016
CountryChina
CityBeijing
Period17/10/1621/10/16
Internet address

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