This course is an elective for both the Smart Systems and Visual Computing and Games Streams.

Autonomous robotics is a very active research area in computer science. It addresses fundamental questions of how an agent can move, navigate, and carry out high-level tasks in unknown and noisy environments. This course will introduce students to algorithms and technologies that have emerged from research in autonomous robotics. These concepts are critical in any study of robotics systems. Further, they have wider applicability in various industries where properties of the real world must be sensed, modelled, and acted upon.

Lab	In addition to classes, this course has one structured laboratory session per week.

Prerequisites:  COMP 2002 or the former COMP 2711, Mathematics 2000, Mathematics 2050, and Statistics 2500 or Statistics 2550

Availability: This course is often offered, but will not be available every academic year.

Course Objectives

This course will introduce students to the fundamental constraints, technologies, and algorithms of autonomous robotics. The focus will be on computational aspects of autonomous wheeled mobile robots. The most important themes will be mobility, perception, and navigation. Assignments will require the implementation of controllers for robots using the Webots and the LEGO Mindstorms NXT robot kits.

Representative Workload

• Assignments (5) 40%
• In-class Exam 20%
• Final Exam 40%

Representative Course Outline

• Introduction:
• Major paradigms in robotics
• Mobility:
• Methods of locomotion
• Kinematics
• Simple control systems
• Perception:
• Sensor technologies
• Stereo vision
• Modelling uncertainty of sensors and positional information
• Localization and Navigation:
• Environmental representation
• Kalman and particle filtering
• Simultaneous localization and mapping (SLAM)
• Motion Planning
• 2-D path planning
• Obstacle avoidance

Page last updated May 24th 2021