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On Visual Area Coverage Using Micro Aerial Vehicles
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-7631-002X
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of this Licentiate is to advance the field of cooperative visual coverage path planners for multiple Micro Aerial Vehicles (MAVs), while aiming for their real life adoption towards the tasks of aerial infrastructure inspection. The fields that will be addressed are focusing in: a) the collaborative perception of the environment, b) the collaborative visual inspection, and c) the optimization of the aerial missions based on the remaining flying battery, camera constraints, coverage constraints and other real life mission induced constraints.

Towards this envisioned aim, this Licentiate will present the following main theoretical contributions: a) centralized and distributed Model Predictive Control (MPC) schemes for the cooperative motion control of MAVs focusing in the establishing of a formation control architecture to enable a dynamic visual sensor from monocular cameras towards a reconfigurable environmental perception, b) revisiting the Cooperative Coverage Path Planning (C-CPP) problem for the inspection of complex infrastructures, c) developing a holistic approach to the problems of 2-D area coverage with MAVs for polygon areas, while considering the camera footprint, and d) designing of a scheme to estimate the Remaining Useful Life (RUL) of the battery during a flight mission, a fact that directly effects the flying capabilities of the MAVs. The theoretical contributions of this thesis have been extensively evaluated in simulation and real life large scale field trials, a direction that adds another contribution of the suggested framework towards the massive insertion of the aerial platforms as aerial tools in the close future.

In the first part of this Licentiate, the vision, motivation, open challenges, contributions, and future works are discussed, while in the second part the full articles connected to the presented contributions in this Licentiate are presented in the annex.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2018.
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-68666ISBN: 978-91-7790-140-2 (print)ISBN: 978-91-7790-141-9 (electronic)OAI: oai:DiVA.org:ltu-68666DiVA, id: diva2:1204286
Presentation
2018-06-15, A1547, Luleå tekniska universitet, Luleå, 09:00 (English)
Opponent
Supervisors
Available from: 2018-05-07 Created: 2018-05-07 Last updated: 2018-05-25Bibliographically approved
List of papers
1. Distributed Model Predictive Control for Unmanned Aerial Vehicles
Open this publication in new window or tab >>Distributed Model Predictive Control for Unmanned Aerial Vehicles
2015 (English)In: 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems: RED-UAS 2015, Cancun, Mexico, 23 - 25 November 2015, Picataway, NJ: IEEE Communications Society, 2015, p. 152-161, article id 7441002Conference paper, Published paper (Refereed)
Abstract [en]

In this article a distributed model pre- dictive control scheme, for the cooperative motion control of Unmanned Aerial Vehicles (UAVs) is be- ing presented. The UAVs are modeled by a 6-DOF nonlinear kinematic model. Two different control ar- chitectures: a centralized and a distributed MPC, are studied and evaluated in simulation experiments. In the centralized approach, one central MPC controller is responsible for the movement coordination of all the UAVs, while in the distributed approach each aerial vehicle plans only for its own actions, while the objective function is coupled with the behavior of the rest of the team members and the constraints are decoupled. In this approach, each agent only shares the future position of itself with the other agents to avoid collisions. For reducing the computation time and complexity, only one step ahead prediction in the corresponding MPC schemes have been considered without a loss of generality. Finally, the efficiency of the overall suggested decentralized MPC scheme, as well as it comparison with the centralized approach, is being evaluated through the utilization of multiple simulation scenarios.

Place, publisher, year, edition, pages
Picataway, NJ: IEEE Communications Society, 2015
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-27817 (URN)10.1109/RED-UAS.2015.7441002 (DOI)000380483900019 ()15eb7a71-2dcd-4d05-8572-fc78100e897a (Local ID)9781509017843 (ISBN)15eb7a71-2dcd-4d05-8572-fc78100e897a (Archive number)15eb7a71-2dcd-4d05-8572-fc78100e897a (OAI)
Conference
Workshop on Research, Education and Development of Unmanned Aerial Systems : 23/11/2015 - 25/11/2015
Note

Validerad; 2016; Nivå 1; 2016-10-11 (andbra)

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-05-07Bibliographically approved
2. Dynamic visual sensing based on MPC controlled UAVs
Open this publication in new window or tab >>Dynamic visual sensing based on MPC controlled UAVs
2017 (English)In: 2017 25th Mediterranean Conference on Control and Automation, MED 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1201-1206, article id 7984281Conference paper, Published paper (Refereed)
Abstract [en]

This article considers the establishment of a dynamic visual sensor from monocular cameras to enable a reconfigurable environmental perception. The cameras are mounted on Micro Aerial Vehicles (MAV) which are coordinated by a Model Predictive Control (MPC) scheme to retain overlapping field of views and form a global sensor with varying baseline. The specific merits of the proposed scheme are: a) the ability to form a configurable stereo rig, according to the application needs, and b) the simple design, the reduction of the payload and the corresponding cost. Moreover, the proposed configurable sensor provides a glpobal 3D reconstruction of the surrounding area, based on a modified Structure from Motion approach. The efficiency of the suggested flexible visual sensor is demonstrated in simulation results that highlight the novel concept of cooperative flying cameras and their 3D reconstruction capabilities

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017
Series
Mediterranean Conference on Control and Automation, ISSN 2325-369X
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-65606 (URN)10.1109/MED.2017.7984281 (DOI)000426926300196 ()2-s2.0-85028515340 (Scopus ID)9781509045334 (ISBN)
Conference
25th Mediterranean Conference on Control and Automation, MED 2017, University of Malta, Valletta, Malta, 3-6 July 2017
Available from: 2017-09-12 Created: 2017-09-12 Last updated: 2018-05-07Bibliographically approved
3. Cooperative coverage path planning for visual inspection
Open this publication in new window or tab >>Cooperative coverage path planning for visual inspection
Show others...
2018 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 74, p. 118-131Article in journal (Refereed) Published
Abstract [en]

This article addresses the inspection problem of a complex 3D infrastructure using multiple Unmanned Aerial Vehicles (UAVs). The main novelty of the proposed scheme stems from the establishment of a theoretical framework capable of providing a path for accomplishing a full coverage of the infrastructure, without any further simplifications (number of considered representation points), by slicing it by horizontal planes to identify branches and assign specific areas to each agent as a solution to an overall optimization problem. Furthermore, the image streams collected during the coverage task are post-processed using Structure from Motion, stereo SLAM and mesh reconstruction algorithms, while the resulting 3D mesh can be used for further visual inspection purposes. The performance of the proposed Collaborative-Coverage Path Planning (C-CPP) has been experimentally evaluated in multiple indoor and realistic outdoor infrastructure inspection experiments and as such it is also contributing significantly towards real life applications for UAVs.

Place, publisher, year, edition, pages
Elsevier, 2018
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-68001 (URN)10.1016/j.conengprac.2018.03.002 (DOI)000430892900011 ()2-s2.0-85043460347 (Scopus ID)
Note

Validerad;2018;Nivå 2;2018-03-19 (andbra)

Available from: 2018-03-19 Created: 2018-03-19 Last updated: 2018-05-14Bibliographically approved
4. Cooperative UAVs as a tool for Aerial Inspection of the Aging Infrastructure
Open this publication in new window or tab >>Cooperative UAVs as a tool for Aerial Inspection of the Aging Infrastructure
Show others...
2017 (English)In: Field and Service Robotics: Results of the 11th International Conference / [ed] Marco Hutter, Roland Siegwart, Cham: Springer, 2017, p. 177-189Conference paper, Published paper (Refereed)
Abstract [en]

This article presents an aerial tool towards the autonomous cooperative coverage and inspection of a 3D infrastructure using multiple Unmanned Aerial Vehicles (UAVs). In the presented approach the UAVs are relying only on their onboard computer and sensory system, deployed for inspection of the 3D structure. In this application each agent covers a different part of the scene autonomously, while avoiding collisions. The visual information collected from the aerial team is collaboratively processed to create the 3D model. The performance of the overall setup has been experimentally evaluated in a realistic outdoor infrastructure inspection experiments, providing sparse and dense 3D reconstruction of the inspected structures.

Place, publisher, year, edition, pages
Cham: Springer, 2017
Series
Springer Proceedings in Advanced Robotics, ISSN 2511-1256 ; 5
National Category
Robotics Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-66211 (URN)10.1007/978-3-319-67361-5_12 (DOI)978-3-319-67360-8 (ISBN)978-3-319-67361-5 (ISBN)
Conference
11th Conference on Field and Service Robotics, FSR 2017, Zürich, 12.-15.9.2017
Available from: 2017-10-22 Created: 2017-10-22 Last updated: 2018-05-07Bibliographically approved
5. On the covering of a polygonal region with fixed size rectangles with an application towards aerial inspection
Open this publication in new window or tab >>On the covering of a polygonal region with fixed size rectangles with an application towards aerial inspection
2017 (English)In: 2017 25th Mediterranean Conference on Control and Automation, MED 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1316-1320, article id 7984300Conference paper, Published paper (Refereed)
Abstract [en]

Unmanned Aerial Vehicles (UAVs) equipped with remote visual sensing can be used in wide range of applications. However, guaranteeing the full coverage of the area and translating this coverage in a path planning problem, it is a quite challenging task. Thus, in this article a well-known and well-investigated family of hard optimization problems, covering a polygonal region (target area) with fixed size rectangles (camera frustrum), is studied. The problem is formulated mathematically and solved using metaheuristic optimization algorithms. The proposed novel algorithmic scheme requires an a priori 2D model of the target area, while it tries to maximize the coverage with a minimum number of fixed size rectangles. Finally, multiple simulation results are presented that prove the efficacy of the proposed scheme

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017
Series
Mediterranean Conference on Control and Automation, ISSN 2325-369X
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-65450 (URN)10.1109/MED.2017.7984284 (DOI)000426926300199 ()2-s2.0-85027893953 (Scopus ID)9781509045334 (ISBN)
Conference
25th Mediterranean Conference on Control and Automation, MED 2017, University of Malta, Valletta, Malta, 3-6 July 2017
Available from: 2017-09-01 Created: 2017-09-01 Last updated: 2018-05-07Bibliographically approved
6. Remaining Useful Battery Life Prediction for UAVs based on Machine Learning*
Open this publication in new window or tab >>Remaining Useful Battery Life Prediction for UAVs based on Machine Learning*
2017 (English)In: IFAC-PapersOnLine, ISSN 1045-0823, E-ISSN 1797-318X, Vol. 50, no 1, p. 4727-4732Article in journal (Refereed) Published
Abstract [en]

Unmanned Aerial Vehicles are becoming part of many industrial applications. The advancements in battery technologies played a crucial part for this trend. However, no matter what the advancements are, all batteries have a fixed capacity and after some time drain out. In order to extend the flying time window, the prediction of the time that the battery will no longer be able to support a flying condition is crucial. This in fact can be cast as a standard Remaining Useful Life prognostic problem, similarly encountered in many fields. In this article, the problem of Remaining Useful Life estimation of a battery, under different flight conditions, is tackled using four machine learning techniques: a linear sparse model, a variant of support vector regression, a multilayer perceptron and an advanced tree based algorithm. The efficiency of the overall proposed machine learning techniques, in the field of batteries prognostics, is evaluated based on multiple experimental data from different flight conditions.

Place, publisher, year, edition, pages
Elsevier, 2017
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-66196 (URN)10.1016/j.ifacol.2017.08.863 (DOI)2-s2.0-85031802665 (Scopus ID)
Conference
20th IFAC World Congress, Toulouse, France, 9-14 July 2017
Note

Konferensartikel i tidskrift

Available from: 2017-10-19 Created: 2017-10-19 Last updated: 2018-05-07Bibliographically approved

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Mansouri, Sina Sharif

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • de-DE
  • en-GB
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Output format
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