ELEC97046 (EE4-60) Human-Centered Robotics
Lecturer(s): Prof Yiannis Demiris
The aim of the course is to teach students the theory and design of robotic systems capable of intelligent interaction with humans, and their application in industrial, medical and rehabilitation settings. The students get the chance to work with research robots to develop systems capable of interacting with humans.
1. Knowledge and understanding outcomes: Students will learn the theory underlying robotic systems that
(a) perceive human states using multimodal interfaces (e.g. computer vision, wearable systems, haptic systems, virtual and augmented reality systems)
(b) model and recognise human actions
(c) use adaptive shared control methods to assist humans in their task
(d) use learning algorithms to improve their performance through interaction with humans.
2. Subject Specific Skills and other attributes:
a) Intellectual skills:
Students will learn to incorporate human factors in the design of their interactive robotic systems, whether in medical, rehabilitation or entertainment settings.
b) Practical Skills:
Students will learn to design and implement control and learning algorithms for interactive robotic systems.
c) Transferable / Key Skills:
Students will learn to work in small groups to incrementally solve large-system (hardware/software) challenges [good programming knowledge is required before registering for the course]
Part A: Fundamentals: Types of Human centered robotics; contact free sharing of workspace, shared manipulation and control, cooperative assembly. Direct physical human-machine contact in medical and rehabilitation robotics. Requirements and performance metrics for human-centered robotics; safety, flexibility, and adaptability to users
Part B: Perception of user state: Interface modalities: electrophysiological signals (ExG), audiovisual signal processing, haptic interfaces. Action recognition and intention prediction using vision. Design and representation of computational models of human actions.
Part C: Control & Learning: Variable autonomy and adaptive shared control methods; Interactive Programming of Robots; Task learning by demonstration; Robot Learning algorithms
Part D: Applications: Medical and Healthcare robotics; Human-Machine Cooperative Systems in Surgery; Rehabilitation robotics; Robot Therapy following Neurological Injury; Manipulation, Mobility and Cognitive Aids
Exam Duration: N/A
Coursework contribution: 100%
Closed or Open Book (end of year exam): N/A
Coursework only module
Oral Exam Required (as final assessment): N/A
Prerequisite module(s): None required
Course Homepage: unavailable