KNOWROB - knowledge processing for autonomous personal robots

Knowledge processing is an essential technique for enabling autonomous robots to do the right thing to the right object in the right way. Using knowledge processing the robots can achieve more flexible and general behavior and better performance. While knowledge representation and reasoning has been a well-established research field in artificial intelligence for several decades, little work has been done to design and realize knowledge processing mechanisms for the use in the context of robotic control. In this paper, we report on KNOWROB, a knowledge processing system particularly designed for autonomous personal robots. KNOWROB is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference - knowledge processing features that are particularly necessary for autonomous robot control.

Authors

• Moritz Tenorth
• Michael Beetz

Keywords

• Knowledge representation
• Robotics and automation
• Robot control
• Artificial intelligence
• Intelligent robots
• Automatic control
• Process design
• Logic
• Knowledge management
• Uncertainty
• Autonomic System
• Personal Robots
• Autonomic Control
• Field Of Artificial Intelligence
• Description Logic
• Data Structure
• Knowledge Base
• Remainder Of This Paper
• Graphical User Interface
• Regression Tree
• Robotic System
• Sensor Networks
• Manipulation Tasks
• Perceptual System
• Radio Frequency Identification
• Calculation Of Properties
• Human Motion
• Environment Map
• Commonsense Knowledge
• Perception Module
• Pose Tracking
• Human Pose
• Inference Task
• Abstract Knowledge
• Radio Frequency Identification Tags
• Physical Body
• Course Of Action
• Laser Ranging