Zelch, Christoph (2017)
Model-Based Optimization of Whole-Body-Poses for Humanoid Robots in Challenging Environments.
Technische Universität Darmstadt
Masterarbeit, Bibliographie
Kurzbeschreibung (Abstract)
The control of complex multi-body systems requires effective and flexible methods to find and reach optimal joint states for a goal posture with some given constraints like static stability. In this thesis, a framework has been developed to optimize general whole-body poses of serial-chain multi-body systems. Specifications of the position and orientation constraints, of the manipulability, of static stability or of self-collision avoidance can be added to a nonlinear optimization problem as constraints or as addend of its objective function. This optimization problem is solved by the commercial solver SNOPT that implements a SQP method. The framework allows an easy integration of new specifications. Further, it is built to be extended by a dynamic robot model, which allows more intricate specifications of postures. A trajectory generator has been implemented that allows a robot to advance safely from a start to a goal posture, since intermediate poses are generated that have to comply with some given constraints. Multiple test scenarios have been created to test the framework using different requirements and considering a majority of the framework’s implemented functionality.
| Typ des Eintrags: | Masterarbeit |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Zelch, Christoph |
| Art des Eintrags: | Bibliographie |
| Titel: | Model-Based Optimization of Whole-Body-Poses for Humanoid Robots in Challenging Environments |
| Sprache: | Englisch |
| Publikationsjahr: | Mai 2017 |
| Ort: | Darmstadt |
| Kurzbeschreibung (Abstract): | The control of complex multi-body systems requires effective and flexible methods to find and reach optimal joint states for a goal posture with some given constraints like static stability. In this thesis, a framework has been developed to optimize general whole-body poses of serial-chain multi-body systems. Specifications of the position and orientation constraints, of the manipulability, of static stability or of self-collision avoidance can be added to a nonlinear optimization problem as constraints or as addend of its objective function. This optimization problem is solved by the commercial solver SNOPT that implements a SQP method. The framework allows an easy integration of new specifications. Further, it is built to be extended by a dynamic robot model, which allows more intricate specifications of postures. A trajectory generator has been implemented that allows a robot to advance safely from a start to a goal posture, since intermediate poses are generated that have to comply with some given constraints. Multiple test scenarios have been created to test the framework using different requirements and considering a majority of the framework’s implemented functionality. |
| Freie Schlagworte: | Humanoid Optimization Control Planning |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik |
| Hinterlegungsdatum: | 06 Jun 2019 06:09 |
| Letzte Änderung: | 06 Jun 2019 06:09 |
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