This course covers knowledge representation and reasoning for cognition-enabled robot manipulation. The learning outcomes include understanding manipulation skills, cognitive architecture, knowledge representation, and symbolic knowledge bases. The course teaches skills such as robot control programs, plan language, supervised learning, and simulation-based reasoning. The teaching method involves lectures on various topics related to robotics. The intended audience for this course is individuals interested in robotics, specifically in the areas of manipulation, cognitive robotics, and knowledge representation.
Overview
Syllabus
Welcome
Introduction
Manipulation
Robot Control Programs
Manipulation Skills
The Key Problem
The Challenge
Cognitive Architecture
Implicit
Low Level
Plan Language
Failure Taxonomy
Inference
Hypothesis
Demonstration
Grounding
Scaling
Supervised Learning
Knowledge Representation
Robots in the Supermarket
Building a Symbolic Knowledge Base
Autonomous Manipulation
RealWorld Environment
Theatre Twin
Simulation Based Reasoning
Symbolic Knowledgebase
Simulation
Mental Simulation
Mental Imagery
Manipulation Tasks
Semantic Representations
Manipulation Actions
Basic System Architecture
Hybrid Infrastructure
Episodic Memory
Data Structure
Searchbased Reasoning
Taught by
Paul G. Allen School
