Module 15267 (2012)
Syllabus page 2012/2013
06-15267
Intelligent Robotics (Extended)
Level 4/M
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus
The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)
Relevant Links
Outline
Aims
The aims of this module are to:
- give an appreciation of the issues that arise when designing complete, physically embodied autonomous agents
- introduce some of the most popular methods for controlling autonomous mobile robots
- give hands on experience of engineering design
- encourage independent thought on possible cognitive architectures for autonomous agents
Learning Outcomes
| On successful completion of this module, the student should be able to: | Assessed by: | |
| 1 | design, build and program simple autonomous robots | Team Project |
| 2 | implement standard signal processing and control algorithms | Team Project |
| 3 | describe and analyse robot processes using appropriate methods | Team Project |
| 4 | write a detailed report on a robot project | Team Project |
| 5 | carry out and write up investigations using appropriate experimental methods | Team Project |
| 6 | describe, use, analyse and discuss the properties of a variety of algorithms in the robotics literature. | Examination |
Restrictions, Prerequisites and Corequisites
Restrictions:
Available only to School of Computer Science students; registration limited to approx. 42 in combination with 06-13520 (Intelligent Robotics). May not be taken by anyone who has taken or is taking 06-13520 (Intelligent Robotics).
Prerequisites:
None
Co-requisites:
None
Teaching
Teaching Methods:
Approximately 27 lectures and 22 laboratory sessions
Contact Hours:
Assessment
- Sessional: 2 hour examination (40%) and continuous assessment (60%)
- Supplementary (where allowed): None; the module may only be repeated.
Recommended Books
| Title | Author(s) | Publisher, Date |
| Probabilistic Robotics | S Thrun, W Burgard, D Fox | MIT Press, 2005 |
| Computational Principles of Mobile Robotics | G Dudek, M Jenkin | Cambridge University Press, 2000 |
| Behavior Based Robotics | R Arkin | MIT Press, 1998 |
| Robotic Explorations: A Hands-on Introduction to Engineering | F Martin | Addison-Wesley, 2001 |
| Vehicles: Experiments in Synthetic Psychology | V Braitenberg | MIT Press, 1984 |
| Mobile Robotics: A practical introduction | U Nehmzow | Springer Verlag, 2000 |
| Robot Learning | S Mahadevan and J Connell | Kluwer Academic, 1993 |
| Mobile Robots: Inspiration to Implementation (2nd ed.) | J Jones, B Seiger and A Flynn | AK Peters, 1999 |
Detailed Syllabus
-
Introduction
- What is robotics?
- Robotics and AI
- Embedded Systems
- Agent-Task-Environment model
- Embodied Systems
- Synthetic approaches to science
- Sensors and signal processing
- Common sensors and their properties
- 1D signal processing
- Vision
- Planning approaches to robot control
- STRIPS and SHAKEY
- Robot kinematics
- Limitations of planning approaches
- Control Theory
- Feedback, feedforward and open loop control
- Linear first order lag processes
- Limitations of control theory
- Probability Based Approaches
- Markov Decision Processes (MDPs)
- Partially Observable Markov Decision Processes
- Navigation using POMDPs
- Kinematics and Motion Planning
- Kinematics of differential drive robots
- Probabilistic road map planning
- Behaviour-Based Control
- The subsumption architecture
- Hybrid architectures
- Formalising behaviour based control
- Adaptive approaches to robot control
- Reinforcement learning for control
- Model based learning approaches to control
- Learning maps
- Evolutionary approaches
- Architectures for control
- CAS
- ROS
- Current research topics
- Learning for manipulation
- Gaze control
- Planning visual search
Last updated: 2012
Source file: /internal/modules/COMSCI/2012/xml/15267.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus