During the last decade we have seen an explosion of all kinds of robots designed for tasks that previously were deemed too challenging for machines. Robots have evolved from robotic arms and karts that could execute repetitive or simple tasks such as painting, welding and vacuum cleaning to autonomous cars, drones and humanoid helpers that execute their tasks in much less controlled and even natural settings. For this modern robots require sophisticated adaptive capabilities.
During this course we will have a thorough look at the important aspects of the robot-architectures used in modern and state of the art robots. The use of various actuators and sensors will be studied. Algorithms for low level tasks such as movement, dead reckoning, obstacle-detection, and balancing will be presented. Intermediate level tasks such as mapping, obstacle recognition and avoidance, and more advanced modes of reckoning, navigation and object manipulation will be studied. Finally, high level tasks such as human-robot-interaction and adaptive behavior in natural environments will be studied and proto-typed using state of the art sensor analysis, computer vision and audio recognition techniques.
After successfully finishing the Robotics course the student:
Has a thorough insight and understanding of the underlying architectures and operating systems of modern state of the art robotic platforms.
Is capable of designing, developing and implementing algorithms for low-, and mid-level robotic tasks on different robotic simulators and platforms.
Has a good understanding of the challenges and progress in robotics research.
Has insights in the design and implementation of high level robotic tasks using state of the art tools for sensor analysis, computer vision and audio recognition techniques.
Is capable of implementing a prototype for autonomous Human Robot Interaction.
The most recent timetable can be found on the students' website.
Note that because of the corona virus outbreak several events such as the YetiBorg Race and final project demo’s will be organized online and remotely.
Mode of instruction
Online Interactive Lectures
Online Interactive Project Team Sessions
Homework and assignments
Hours of study: 168 (= 6 EC)
Practical work: 72
Other (self-study): 70
The final grade is based on:
2 online workshops (20% of the grade)
A remote YetiBorg Race (20% of the grade)
Robotics Project (60% of the grade)
Conferences and journals on Robotics.
- You have to sign up for courses and exams (including retakes) in uSis. Check this link for information about how to register for courses.