Monografie
XPERSIF: a software integration framework & architecture for robotic learning by experimentation
- Language
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Englisch
- ISBN
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1869-5272
- Identifier
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1051215854
- Series
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Technical Report / University of Applied Sciences Bonn-Rhein-Sieg, Department of Computer Science; 02-2008
Subject
Robotik
Contributor
- URN
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
26.01.2023, 1:58 PM CET
Object type
- Monografie
Other Objects (12)
A computational model of robotic surprise
Learning qualitative models by an autonomous robot
Autonomous exploration and inspection
Improving reliability of mobile manipulators against unknown external faults
Fault reasoning based on naive physics
Methods for failure detection for mobile manipulation
Improving reliability of mobile manipulators against unknown external faults
Autonomous exploration and inspection
Methods for failure detection for mobile manipulation
Design of a declarative language for task-oriented grasping and tool-use with dextrous robotic hands
Active tracking with accelerated image processing in hardware
ProSyWis: Concept and Prototype for Managing Knowledge-Intensive Processes
A computational model of robotic surprise
Learning qualitative models by an autonomous robot
Autonomous exploration and inspection
Improving reliability of mobile manipulators against unknown external faults
Fault reasoning based on naive physics
Methods for failure detection for mobile manipulation
Improving reliability of mobile manipulators against unknown external faults
Autonomous exploration and inspection
Methods for failure detection for mobile manipulation
Design of a declarative language for task-oriented grasping and tool-use with dextrous robotic hands
Active tracking with accelerated image processing in hardware
ProSyWis: Concept and Prototype for Managing Knowledge-Intensive Processes
A computational model of robotic surprise
Learning qualitative models by an autonomous robot
Autonomous exploration and inspection
Improving reliability of mobile manipulators against unknown external faults
Fault reasoning based on naive physics
Methods for failure detection for mobile manipulation
Improving reliability of mobile manipulators against unknown external faults
Autonomous exploration and inspection
Methods for failure detection for mobile manipulation
Design of a declarative language for task-oriented grasping and tool-use with dextrous robotic hands
Active tracking with accelerated image processing in hardware