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From Motion Planning to Control - A Navigation Framework for an Autonomous Unmanned Aerial Vehicle
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, AUTTEK - Autonomous Unmanned Aerial Vehicle Research Group .
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2006 (English)In: Proceedings of the 21st Bristol UAV Systems Conference (UAVS), 2006Conference paper, Published paper (Refereed)
Abstract [en]

The use of Unmanned Aerial Vehicles (UAVs) which can operate autonomously in dynamic and complex operational environments is becoming increasingly more common. While the application domains in which they are currently used are still predominantly military in nature, in the future we can expect wide spread usage in thecivil and commercial sectors. In order to insert such vehicles into commercial airspace, it is inherently important that these vehicles can generate collision-free motion plans and also be able to modify such plans during theirexecution in order to deal with contingencies which arise during the course of operation. In this paper, wepresent a fully deployed autonomous unmanned aerial vehicle, based on a Yamaha RMAX helicopter, whichis capable of navigation in urban environments. We describe a motion planning framework which integrates two sample-based motion planning techniques, Probabilistic Roadmaps and Rapidly Exploring Random Treestogether with a path following controller that is used during path execution. Integrating deliberative services, suchas planners, seamlessly with control components in autonomous architectures is currently one of the major open problems in robotics research. We show how the integration between the motion planning framework and thecontrol kernel is done in our system.

Additionally, we incorporate a dynamic path reconfigurability scheme. It offers a surprisingly efficient method for dynamic replanning of a motion plan based on unforeseen contingencies which may arise during the execution of a plan. Those contingencies can be inserted via ground operator/UAV interaction to dynamically change UAV flight paths on the fly. The system has been verified through simulation and in actual flight. We present empirical results of the performance of the framework and the path following controller.

Place, publisher, year, edition, pages
2006.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-36792Local ID: 32592OAI: oai:DiVA.org:liu-36792DiVA, id: diva2:257641
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2023-05-25Bibliographically approved
In thesis
1. Navigation Functionalities for an Autonomous UAV Helicopter
Open this publication in new window or tab >>Navigation Functionalities for an Autonomous UAV Helicopter
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis was written during the WITAS UAV Project where one of the goals has been the development of a software/hardware architecture for an unmanned autonomous helicopter, in addition to autonomous functionalities required for complex mission scenarios. The algorithms developed here have been tested on an unmanned helicopter platform developed by Yamaha Motor Company called the RMAX. The character of the thesis is primarily experimental and it should be viewed as developing navigational functionality to support autonomous flight during complex real world mission scenarios. This task is multidisciplinary since it requires competence in aeronautics, computer science and electronics. The focus of the thesis has been on the development of a control method to enable the helicopter to follow 3D paths. Additionally, a helicopter simulation tool has been developed in order to test the control system before flight-tests. The thesis also presents an implementation and experimental evaluation of a sensor fusion technique based on a Kalman filter applied to a vision based autonomous landing problem. Extensive experimental flight-test results are presented.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2007. p. 107
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1307
Keywords
Unmanned Aerial Vehicle, Control System, Path Following, Path Planning, Sensor Fusion, Vision Based Landing, Kalman Filter, Real-Time
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-21966 (URN)LiU-Tek-Lic-2007:16 (Local ID)9789185715350 (ISBN)LiU-Tek-Lic-2007:16 (Archive number)LiU-Tek-Lic-2007:16 (OAI)
Presentation
2007-03-30, Alan Turing, hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2009-10-15 Created: 2009-10-07 Last updated: 2020-07-03Bibliographically approved
2. Selected Functionalities for Autonomous Intelligent Systems in Public Safety Scenarios
Open this publication in new window or tab >>Selected Functionalities for Autonomous Intelligent Systems in Public Safety Scenarios
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The public safety and security application domain is an important research area that provides great benefits to society. Within this application domain, governmental and non‐governmental agencies, such as blue light organizations (e.g., police or firefighters), are often tasked with essential life‐saving activities when responding to fallouts of natural or man‐made disasters, such as earthquakes, floods, or hurricanes. 

Recent technological advances in artificial intelligence and robotics offer novel tools that first responder teams can use to shorten response times and improve the effectiveness of rescue efforts. Modern first responder teams are increasingly being supported by autonomous intelligent systems such as ground robots or Unmanned Aerial Vehicles (UAVs). However, even though many commercial systems are available and used in real deployments, many important research questions still need to be answered. These relate to both autonomous intelligent system design and development in addition to how such systems can be used in the context of public safety applications. 

This thesis presents a collection of functionalities for autonomous intelligent systems in public safety scenarios. Contributions in this thesis are divided into two parts. In Part 1, we focus on the design of navigation frameworks for UAVs for solving the problem of autonomous navigation in dynamic or changing environments. In particular, we present several novel ideas for integrating motion planning, control, and perception functionalities within robotic architectures to solve navigation tasks efficiently. 

In Part 2, we concentrate on an important service that autonomous intelligent systems can offer to first responder teams. Specifically, we focus on base functionalities required for UAV‐based rapid ad hoc communication infrastructure deployment in the initial phases of rescue operations. The main idea is to use heterogeneous teams of UAVs to deploy communication nodes that include routers and are used to establish ad hoc Wireless Mesh Networks (WMNs). We consider fundamental problems related to WMN network design, such as calculating node placements, and propose efficient novel algorithms to solve these problems. 

Considerable effort has been put into applying the developed techniques in real systems and scenarios. Thus, the approaches presented in this thesis have been validated through extensive simulations and real‐world experimentation with various UAV systems. Several contributions presented in the thesis are generic and can be adapted to other autonomous intelligent system types and application domains other than public safety and security. 

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2023. p. 69
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2322
National Category
Computer Vision and Robotics (Autonomous Systems) Computer Sciences
Identifiers
urn:nbn:se:liu:diva-194100 (URN)10.3384/9789180751964 (DOI)9789180751957 (ISBN)9789180751964 (ISBN)
Public defence
2023-06-14, Ada Lovelace, B-building, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Note

Funding: This work has been supported by the ELLIIT Network Organization for Information and Communication Technology, Sweden (Project B09), and Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation, in addi‐tion to the sources already acknowledged in the individual papers.

Available from: 2023-05-25 Created: 2023-05-25 Last updated: 2023-05-26Bibliographically approved

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Wzorek, MariuszConte, GianpaoloRudol, PiotrMerz, TorstenDuranti, SimoneDoherty, Patrick

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