Aerial navigation in obstructed environments with embedded nonlinear model predictive control

Elias Small, Pantelis Sopasakis, Emil Fresk, Panagiotis Patrinos, George Nikolakopoulos

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

19 Citations (Scopus)
241 Downloads (Pure)


We propose a methodology for autonomous aerial navigation and obstacle avoidance of micro aerial vehicles (MAV) using nonlinear model predictive control (NMPC) and we demonstrate its effectiveness with laboratory experiments. The proposed methodology can accommodate obstacles of arbitrary, potentially non-convex, geometry. The NMPC problem is solved using PANOC: a fast numerical optimization method which is completely matrix-free, is not sensitive to ill conditioning, involves only simple algebraic operations and is suitable for embedded NMPC. A C89 implementation of PANOC solves the NMPC problem at a rate of 20Hz on board a lab-scale MAV. The MAV performs smooth maneuvers moving around an obstacle. For increased autonomy, we propose a simple method to compensate for the reduction of thrust over time, which comes from the depletion of the MAV's battery, by estimating the thrust constant.
Original languageEnglish
Title of host publication European Control Conference 25/06/2018 → 28/06/2019 Naples, Italy
Publisher IEEE
Number of pages8
ISBN (Electronic)978-3-907144-00-8
ISBN (Print)978-1-7281-1314-2
Publication statusPublished - 15 Aug 2019
EventEuropean Control Conference - Hotel Royal Continental, Naples, Naples, Italy
Duration: 25 Jun 201828 Jun 2019


ConferenceEuropean Control Conference
Abbreviated titleECC
Internet address


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