Drittmittelprojekt | beendet | 01.03.2010
- 28.02.2014
Adaptive Modular Architecture for Rich Motor Skills (AMARSi)
Projektleitung
Steil, Jochen
Koordinierende Einrichtung
Zweck
Forschung
Fachgebiete
Förderung
Mittelgeber:
Europäische Union
Förderprogramm:
Drittmittel EU und sonst. internat. Organisationen
Cognitive Systems and Robotics
Richness of biological motor behavior in robotic systems
The motor skills of today’s robots still must be qualified as poor. The AMARSi Integrated Project aims at a qualitative jump toward biological richness of robotic motor skills. To achieve this goal, a number of innovative scientific concepts and interdisciplinary research methods will be implemented.
Acquiring rich motor skills will change the role of robots in our human’s society in two fundamental ways. First, such robots will be much more versatile than today, with greatly expanded ranges of practical usages. And second, the naturalness and compliance of their motor behavior will make them blend into the everyday routines of human society, physically safe and psychologically acceptable.
Richness of biological motor behavior in robotic systems
The motor skills of today’s robots still must be qualified as poor. The AMARSi Integrated Project aims at a qualitative jump toward biological richness of robotic motor skills. To achieve this goal, a number of innovative scientific concepts and interdisciplinary research methods will be implemented.
Acquiring rich motor skills will change the role of robots in our human’s society in two fundamental ways. First, such robots will be much more versatile than today, with greatly expanded ranges of practical usages. And second, the naturalness and compliance of their motor behavior will make them blend into the everyday routines of human society, physically safe and psychologically acceptable.
- Mukovskiy A, Land WM, Schack T, Giese MA. Modeling of predictive human movement coordination patterns for applications in computer graphics. Journal of WSCG. 2015;23(2):139-146.
- Lemme A, Meirovitch Y, Khansari-Zadeh SM, Flash T, Billard A, Steil JJ. Open-source benchmarking for learned reaching motion generation in robotics. Paladyn, Journal of Behavioral Robotics. 2015;6(1):30-41.
- Nordmann A, Tuleu A, Wrede S. A Domain-Specific Language and Simulation Architecture for the Oncilla Robot. In: ICRA 2013 Workshop on Developments of Simulation Tools for Robotics & Biomechanics. 2013.
- Nordmann A, Wrede S. A Domain-Specific Language for Rich Motor Skill Architectures. Presented at the 3rd International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob), Tsukuba, Japan.
- Wienke J, Nordmann A, Wrede S. A Meta-Model and Toolchain for Improved Interoperability of Robotic Frameworks. In: Noda I, Ando N, Brugali D, Kuffner J, eds. Simulation, Modeling, and Programming for Autonomous Robots. Lecture Notes in Computer Science. Vol 7628. Berlin: Springer Berlin Heidelberg; 2012: 323-334.
- Nordmann A, Wrede S. Meta-model and Software Concepts for an Adaptive Component Architecture.; 2011.
- Nordmann A, Wrede S, Tsagarakis NG, Tuleu A. Software Interface for Proprioceptive Sensors and Actuators.; 2010.
Cognitive Systems and Robotics
Richness of biological motor behavior in robotic systems
The motor skills of today’s robots still must be qualified as poor. The AMARSi Integrated Project aims at a qualitative jump toward biological richness of robotic motor skills. To achieve this goal, a number of innovative scientific concepts and interdisciplinary research methods will be implemented.
Acquiring rich motor skills will change the role of robots in our human’s society in two fundamental ways. First, such robots will be much more versatile than today, with greatly expanded ranges of practical usages. And second, the naturalness and compliance of their motor behavior will make them blend into the everyday routines of human society, physically safe and psychologically acceptable.
Richness of biological motor behavior in robotic systems
The motor skills of today’s robots still must be qualified as poor. The AMARSi Integrated Project aims at a qualitative jump toward biological richness of robotic motor skills. To achieve this goal, a number of innovative scientific concepts and interdisciplinary research methods will be implemented.
Acquiring rich motor skills will change the role of robots in our human’s society in two fundamental ways. First, such robots will be much more versatile than today, with greatly expanded ranges of practical usages. And second, the naturalness and compliance of their motor behavior will make them blend into the everyday routines of human society, physically safe and psychologically acceptable.
- Mukovskiy A, Land WM, Schack T, Giese MA. Modeling of predictive human movement coordination patterns for applications in computer graphics. Journal of WSCG. 2015;23(2):139-146.
- Lemme A, Meirovitch Y, Khansari-Zadeh SM, Flash T, Billard A, Steil JJ. Open-source benchmarking for learned reaching motion generation in robotics. Paladyn, Journal of Behavioral Robotics. 2015;6(1):30-41.
- Nordmann A, Tuleu A, Wrede S. A Domain-Specific Language and Simulation Architecture for the Oncilla Robot. In: ICRA 2013 Workshop on Developments of Simulation Tools for Robotics & Biomechanics. 2013.
- Nordmann A, Wrede S. A Domain-Specific Language for Rich Motor Skill Architectures. Presented at the 3rd International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob), Tsukuba, Japan.
- Wienke J, Nordmann A, Wrede S. A Meta-Model and Toolchain for Improved Interoperability of Robotic Frameworks. In: Noda I, Ando N, Brugali D, Kuffner J, eds. Simulation, Modeling, and Programming for Autonomous Robots. Lecture Notes in Computer Science. Vol 7628. Berlin: Springer Berlin Heidelberg; 2012: 323-334.
- Nordmann A, Wrede S. Meta-model and Software Concepts for an Adaptive Component Architecture.; 2011.
- Nordmann A, Wrede S, Tsagarakis NG, Tuleu A. Software Interface for Proprioceptive Sensors and Actuators.; 2010.