Ommer, Nicolai (2016)
A Framework for Adaptive Feedforward Motor-Control for Unmanned Ground Vehicles.
Technische Universität Darmstadt
Masterarbeit, Bibliographie
Kurzbeschreibung (Abstract)
Autonomous robots require precise motion models to interact in their environment. Deviations from their planned path may result in collisions or inefficient motion trajectories. Motion control underlies uncertainties such as unknown ground, contact forces, hardware inaccuracies and hardware wear that can be addressed by a learned compensation model to improve accuracy. While there are many proposals for learning a motion model offline, in recent years online learning methods became more widespread. These methods enable adaptation during runtime to compensate hardware failures or to adapt to new terrain. In this thesis different online learning methods were integrated into a new framework based on ROS (Robot Operating System) for an online adaptive feedforward controller which is based on an adaptive compensation model. The framework was applied to an omnidirectional soccer robot and a tracked rescue robot, but is designed to be applicable to other systems as well.
| Typ des Eintrags: | Masterarbeit |
|---|---|
| Erschienen: | 2016 |
| Autor(en): | Ommer, Nicolai |
| Art des Eintrags: | Bibliographie |
| Titel: | A Framework for Adaptive Feedforward Motor-Control for Unmanned Ground Vehicles |
| Sprache: | Englisch |
| Publikationsjahr: | September 2016 |
| Ort: | Department of Computer Science (SIM |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Autonomous robots require precise motion models to interact in their environment. Deviations from their planned path may result in collisions or inefficient motion trajectories. Motion control underlies uncertainties such as unknown ground, contact forces, hardware inaccuracies and hardware wear that can be addressed by a learned compensation model to improve accuracy. While there are many proposals for learning a motion model offline, in recent years online learning methods became more widespread. These methods enable adaptation during runtime to compensate hardware failures or to adapt to new terrain. In this thesis different online learning methods were integrated into a new framework based on ROS (Robot Operating System) for an online adaptive feedforward controller which is based on an adaptive compensation model. The framework was applied to an omnidirectional soccer robot and a tracked rescue robot, but is designed to be applicable to other systems as well. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik |
| Hinterlegungsdatum: | 26 Jun 2019 07:47 |
| Letzte Änderung: | 26 Jun 2019 07:47 |
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