Authors:
Thomas Müller
;
Binh An Tran
and
Alois Knoll
Affiliation:
Technische Universität München, Germany
Keyword(s):
Flexible automation, Parallel processing, Realtime actuator control, Limp object handling.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Industrial Networks and Automation
;
Informatics in Control, Automation and Robotics
;
Real-Time Systems Control
;
Robot Design, Development and Control
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
;
Telerobotics and Teleoperation
Abstract:
In this paper, an intrinsically parallel framework striving for increased flexibility in development of robotic, computer vision, and machine intelligence applications is introduced. The framework comprises a generic set of tools for realtime data acquisition, robot control, integration of external software components and task automation. The primary goal is to provide a developer- and user-friendly, but yet efficient base architecture for complex AI system implementations, be it for research, educational, or industrial purposes. The system
therefore combines promising ideas of recent neuroscientific research with a blackboard information storage mechanism, an implementation of the multi-agent paradigm, and graphical user interaction. Furthermore, the paper elaborates on how the framework’s building blocks can be composed to applications of increasing complexity. The final target application includes parallel image processing, actuator control, and reasoning to handle limp objects a
nd automate handling-tasks within dynamic scenarios.
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