Lossless convexification of quadrotor motion planning with experiments

This thesis describes a motion planning method that is designed to guide an autonomous quadrotor. The proposed method is based on a novel lossless convexication, which was first introduced in (12), that allows convex representations of many non-convex control constraints, such as that of the quadrot...

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Main Author: Pehlivantürk, Can
Format: Others
Language:en
Published: 2014
Subjects:
UAV
Online Access:http://hdl.handle.net/2152/26388
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spelling ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-263882015-09-20T17:26:49ZLossless convexification of quadrotor motion planning with experimentsPehlivantürk, CanQuadrotorUAVTrajectory generationConvexificationThis thesis describes a motion planning method that is designed to guide an autonomous quadrotor. The proposed method is based on a novel lossless convexication, which was first introduced in (12), that allows convex representations of many non-convex control constraints, such as that of the quadrotors. The second contribution of this thesis is to include two separate methods to generate path constraints that capture non-convex position constraints. Using the convexied optimal trajectory generation problem with physical and path constraints, an algorithm is developed that generates fuel optimal trajectories given the initial state and desired final state. As a proof of concept, a quadrotor testbed is developed that utilize a state-of-the-art motion tracking system. The quadrotor is commanded via a ground station where the convexified optimal trajectory generation algorithm is successfully implemented together with a trajectory tracking feedback controller.text2014-10-09T16:18:38Z2014-082014-09-04August 20142014-10-09T16:18:38ZThesisapplication/pdfhttp://hdl.handle.net/2152/26388en
collection NDLTD
language en
format Others
sources NDLTD
topic Quadrotor
UAV
Trajectory generation
Convexification
spellingShingle Quadrotor
UAV
Trajectory generation
Convexification
Pehlivantürk, Can
Lossless convexification of quadrotor motion planning with experiments
description This thesis describes a motion planning method that is designed to guide an autonomous quadrotor. The proposed method is based on a novel lossless convexication, which was first introduced in (12), that allows convex representations of many non-convex control constraints, such as that of the quadrotors. The second contribution of this thesis is to include two separate methods to generate path constraints that capture non-convex position constraints. Using the convexied optimal trajectory generation problem with physical and path constraints, an algorithm is developed that generates fuel optimal trajectories given the initial state and desired final state. As a proof of concept, a quadrotor testbed is developed that utilize a state-of-the-art motion tracking system. The quadrotor is commanded via a ground station where the convexified optimal trajectory generation algorithm is successfully implemented together with a trajectory tracking feedback controller. === text
author Pehlivantürk, Can
author_facet Pehlivantürk, Can
author_sort Pehlivantürk, Can
title Lossless convexification of quadrotor motion planning with experiments
title_short Lossless convexification of quadrotor motion planning with experiments
title_full Lossless convexification of quadrotor motion planning with experiments
title_fullStr Lossless convexification of quadrotor motion planning with experiments
title_full_unstemmed Lossless convexification of quadrotor motion planning with experiments
title_sort lossless convexification of quadrotor motion planning with experiments
publishDate 2014
url http://hdl.handle.net/2152/26388
work_keys_str_mv AT pehlivanturkcan losslessconvexificationofquadrotormotionplanningwithexperiments
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