Intelligent Machines

This course introduces robotics and cyber-physical systems through hands-on lab activities, assignments, projects, and guest lectures spanning research and practice. Topics include sensors and actuators, system modelling, kinematics, dynamics and controls, perception, planning and navigation, cyber-physical systems, communication, and hardware. Students graduate from the course able to design, build, and evaluate simple robotic and cyber-physical systems.

Course Overview

The course introduces the foundations of robotics and cyber-physical systems, covering sensing, actuation, modelling, controls, planning, mapping and localization. Through lectures and hands-on laboratories, students learn how these components work together to design autonomous robotic systems and gain practical experience by building and evaluating simple robots.

Learning Objectives

  • Understand the fundamental problems in robotics and cyber-physical systems.
  • Apply algorithms and methods to build simple robotic systems.
  • Analyze the suitability of different robotic methods for practical scenarios.
  • Synthesize multiple algorithms to develop autonomous robotic systems.

Learning Outcomes

  • Explain fundamental robotics problems and solution approaches | Knowledge Outcome
  • Demonstrate robotic solutions through laboratory implementation | Comprehend Outcome
  • Apply concepts to assignments and examinations | Apply Outcome
  • Build simple robotic systems for assigned projects | Apply Outcome
  • Evaluate appropriate methods for different robotic applications | Evaluate Outcome
  • Synthesize algorithms to develop autonomous robots | Create/Synthesize Outcome

There is no required textbook. Students are encouraged to refer to the recommended references provided in the course outline.

  • Gregory Dudek and Michael Jenkin, Computational Principles of Mobile Robotics.
  • Katsuhiko Ogata, Modern Control Engineering.
  • Francesco Bullo and Stephen L. Smith, Robotic Planning and Kinematics.
  • Howie Choset et al., Principles of Robot Motion.

Assessments and Grading

  • Exams: 50%
  • Projects: 25%
  • Assignments/Quizzes: 15%
  • Attendance: 10% (mandatory)

Relative grading applies. 

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