Abstract
In this paper, we present an onboard robust nonlinear control approach for quadrotor Unmanned Aerial Vehicles (UAVs) in the environments with disturbances and obstacles. The complete framework consists of an attitude controller based on the solution of global output regulation problems for SO(3), a backstepping-like position controller, a 6-dimensional wrench observer to estimate the unknown force and torque disturbances, and an online trajectory planner based on a model predictive control method with obstacle avoiding constraints. We prove the strong convergence properties of the proposed method both in theory and via real-robot experiments. The control approach is onboard implemented on a quadrotor UAV, and has been validated through intensive experiments and compared with other nonlinear control methods for waypoint navigation and large-tilted path following tasks in the presence of external disturbances, e.g. wind gusts. The presented approach has also been evaluated in the scenarios with randomly located obstacles.
| Original language | English |
|---|---|
| Pages (from-to) | 317-332 |
| Number of pages | 16 |
| Journal | Robotics and Autonomous Systems |
| Volume | 98 |
| DOIs | |
| Publication status | Published - 2017 Dec |
| Externally published | Yes |
Bibliographical note
Funding Information:The following is the Supplementary material related to this article. MMC S1 Five cases of experimental evaluations on a quadrotor UAV for the proposed robust control approach. Case 1: Validation of nonlinear wrench observer; Case 2: Experiment of hovering with external wind gusts; Case 2: Experiment of point-to-point waypoint navigation; Case 4: Experiment of aggressive path following; Case 5: typical scenarios in the experiments of waypoint navigation in complex scenarios with obstacles. Yuyi Liu received his bachelor degrees at Fudan University and University of Birmingham in 2011. He thereafter received his master degree in aeronautical engineering from Imperial College London in 2012. He had a research stay at Katholieke Universiteit Leuven in 2013. He is currently working as a research assistant at the University of Tübingen and Max Planck Institute for Biological Cybernetics. His research is focused on the onboard implementation of fast model predictive control and formation control algorithms on aerial robots. Sujit Rajappa studied Electronics and Instrumentation at Anna University, MIT Campus, India from 2004–2008 where he received his B.Eng. degree. From 2008–2011, he worked as Control Engineer in Honeywell Automation. In 2013, he received his M.Sc. in Automatic Control and Robotics at Ecole Centrale de Nantes, France. He is currently working as a researcher at the Max Planck Institute for Biological Cybernetics. His current research is focused in the Aerial Robotics domain with the development of nonlinear control techniques, fully actuated UAV platforms and Human–UAV physical interaction. Jan Maximilian Montenbruck received his undergraduate education at University of Duisburg-Essen and Pennsylvania State University, thereafter pursuing his master degree at University of Duisburg-Essen and Harvard University. In 2016, he obtained his doctoral degree from the University of Stuttgart, where he now serves as postdoctoral researcher and lecturer. His research interests are in the area of systems and control theory. Paolo Stegagno received the Ph.D. degree in System Engineering from Sapienza University of Rome, Italy, in 2012. In 2010 he was Visiting Scholar at the University of Minnesota, USA. From 2012 to 2013 he was a post-doc at Sapienza University of Rome. Between July 2013 and June 2016 he has been a Research Scientist in the Autonomous Robotics and Human–Machine Systems group at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, and Project Leader of the group since 2014. Since September 2016 he is a Post-Doctoral Fellow at the department of Ocean Engineering, University of Rhode Island. His main research interests include mobile robotics, multi-robot systems, and unmanned aerial vehicles, with a focus on sensing, estimation and localization. Since 2014, he is Associate Editor for the IEEE/RSJ International Conference on Intelligent Robots and Systems. Heinrich Bülthoff holds a Ph.D. degree in the natural sciences from the Eberhard Karls Universität in Tübingen. From 1980 to 1988 he worked as a research scientist at the Max Planck Institute for Biological Cybernetics and the Massachusetts Institute of Technology. He was Assistant, Associate and Full Professor of Cognitive Science at Brown University in Providence from 1988–1993. He is scientific member of the Max Planck Society and director at the Max Planck Institute for Biological Cybernetics in Tübingen. He is head of the Department Human Perception, Cognition and Action. He is Honorary Professor at the Eberhard Karls Universität in Tübingen and at the Korea University in Seoul. Heinrich Bülthoff is editor of several international journals and is involved in many international collaborations as well as being a member of many national and international University boards. Frank Allgöwer received the B.S. degree in engineering cybernetics from the University of Stuttgart, Stuttgart, Germany, the M.S. degree in applied mathematics from the University of California Los Angeles (UCLA), Los Angeles, CA, USA, and the Ph.D. degree from the University of Stuttgart, Stuttgart, Germany. He is the Director of the Institute for Systems Theory and Automatic Control and Executive Director of the Stuttgart Research Centre Systems Biology at the University of Stuttgart. His research interests include cooperative control, predictive control, and nonlinear control with application to a wide range of fields including systems biology. Dr. Allgwer is currently President Elect of the International Federation of Automatic Control IFAC and serves as Vice President of the German Research Foundation DFG. Andreas Zell received the diploma in computer science from the University of Kaiserslautern, Germany, in 1986, a M.S. degree in symbolic and heuristic computation from Stanford University, USA, in 1987, and a Ph.D. in computer science from the University of Stuttgart, Germany in 1989. From 1990–1994 he was lecturer and later assistant professor at the University of Stuttgart. He received his habilitation (venia legendi) in 1994 and since 1995 he has been appointed as full professor at the Eberhard Karls Universität Tübingen, now at the chair of cognitive systems. His research interests are mobile robots, robot vision, navigation and SLAM, artificial neural networks, evolutionary algorithms and machine learning in general. As founding director of the Centre for bioinformatics Tübingen he used machine learning for many bioinformatics applications but is now concentrating on cognitive robotics and deep learning for technical applications.
Publisher Copyright:
© 2017 Elsevier B.V.
Keywords
- Aerial robotics
- Nonlinear observer
- Obstacle avoidance
- Robust control
- Unmanned Aerial Vehicles
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- General Mathematics
- Computer Science Applications