Vision for Autonomous Robots

Course manual 2025/2026

Course content

For a robot to be autonomous, it has to perceive and understand the world around it. This course introduces you to the key computer vision algorithms used in mobile robotics, such as information filtering, feature extraction, multiple view geometry, scene reconstruction, object tracking, visual-inertial odometry, Simultaneous Localization And Mapping (SLAM), based on the latest development of deep learning.

See for more information: Course website

Study materials

Literature

• Peter Corke, Robotics, Vision and Control - Fundamental Algorithms in Python, Springer Tracts in Advanced Robotics 146, 3rd edition, May 2023

• Sumplementary

  Gregory Dudek and Michael Jenkin, Computational Principles of Mobile Robotics, Cambridge University Press, 3rd edition, February 2024.

Software

• Python, ROS2

Other

• UGV Rover

Objectives

• The student has the capability to develop perception algorithms for robot systems
• The student can formulate scientific questions on perception algorithms for robot systems to decompose and solve such complex problems
• The student can analyze and solve problems in coupling perception algorithms with the appropriate actions to navigate the environment
• The student can apply and demonstrate the learned knowledge and skills in practical robotics applications
• The student can critically appraise current research literature on the state of the art perception algorithms on a robotic platform

Teaching methods

• Lecture
• Computer lab session/practical training
• Presentation/symposium

Learning activities

Attendance

This programme does not have requirements concerning attendance (OER part B).

Assessment

Assignments

The assignments will be done in groups of four.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Contact information

Coordinator

• dr. Arnoud Visser

Staff

• dr. Shaodi You