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Real-time AI for Robotics and Simulated Environments

Language

English

Course format On-site
Date 2021-01-11 - 2021-05-07

Course content

  • Robotic control mechanisms
  • Simulation environments
  • Real time knowledge representation
  • Real time decision making and search
  • Real time scheduling and allocation
  • Decision making under uncertainty
  • Autonomous aerial, ground and underwater robots

Learning outcomes

Having completed the course, the candidate should have:

Knowledge:

  • The candidate is in the forefront of knowledge within the fields of artificial intelligence in robotics and simulated environments.
  • The candidate can evaluate the expediency and application of robotic control mechanisms, aspects of simulated environments, real-time decision making and planning mechanisms, temporal representations in research and development projects.
  • The candidate has the ability to discuss and explain robotic control mechanisms, aspects of simulated environments, real-time decision making and planning mechanisms, temporal representations methods.

Skills:

  • The candidate can formulate real time computational problems using robots and simulation environments.
  • The candidate can implement real time solutions to complex problems in various robotic and simulation domains.

General competence:

  • The candidate has the ability to communicate and lead discussions on recent research about computational real time decision making in robotic and simulation environments.
  • The candidate has the ability to evaluate and critique mechanisms for real time problem solving for various domains using robotics and simulations.

Prerequisites

Fundamental programming and algorithms

Admission to a programme of study is required:

  • Computer Science (PHD-CS)
  • Information Security (PHD-IS)
  • Information Security and Communication (PHISCT)

Files/Documents

ISCED Categories

Machinery and operators