Course syllabus - Mobile Robotics

Objectives

The purpose of the course is to provide fundamental knowledge on how the different typologies of mobile robots are designed and controlled to perform autonomous tasks in the different areas like field robotics, service robotics, medial robotics, bio-inspired robotics, etc. In particular, locomotion strategies will be analyzed for wheeled and legged robots, with particular attention to climbing robots, quadruped and biped locomotion, balancing and gait analysis, and humanoid robots.
Differently from industrial robots, localization and pose estimation is a crucial problem in mobile robotics, so methods for sensors fusion and 3D mapping will be presented. To this purpose specific attention will be reserved to computer vision; in particular, monocular and binocular vision will be presented together the fundamental algorithms for image processing, features extraction and tracking, motion estimation and 3D reconstruction. Among others, specific attention will be reserved to unmanned aerial vehicles and underwater robots, since exploiting a full 6D pose estimation. Once the robot is localized in a reconstructed 3D environment, fundamental methods for path planning and obstacle detection/avoidance will be needed and provided by the course.

Learning outcomes

After completing the course, the student will be able to:

- model a mobile robot using different kinds of kinematic structures
- analyze the motion capabilities and the main advantages/disadvantages of the different configurations (wheels, legs, hybrid, passive, balancing, flying, etc) and distinguish different locomotion strategies
- describe the problems related to biped locomotion, walking and running for modern humanoid robots
- describe and implement fundamental algorithms for localization and mapping
- use image processing for estimating the motion of a moving robot
- reconstruct a 3D environment fusing for a set of sensory data
- implement basic methods for obstacle detection and avoidance

Course content

Mobile robots typologies, non holonomic constraints, wheeled robot configurations, legged robots, hybrid robots, biped robots, balancing robots. Fundamentals of climbing robots. Biomechanics of biped locomotion, gait analysis, walking and running, humanoids. Compliancy in locomotion, variable stiffness actuators. Passivity and under-actuation in robotics.
SLAM (simultaneous localization and mapping), odometric localization, probabilistic localization, EKF (extended kalman filtering), particle filtering.
Fundamentals of computer vision, image processing, features extraction, tracking, segmentation, objects descriptors and recognition. Camera calibration, multiple view geometry, monocular vision, binocular vision, epipolar geometry, multiple view geometry. Fundamentals of 3D reconstruction, SFM (structure from motion), VO (visual odometry), egomotion estimation, optical flow, BA (bundle adjustment) based SLAM. Range cameras fundamentals, Kinect sensor, RGB-D SLAM. Path planning, b-splines, obstacle avoidance fundamentals, potential fields.  Roboethics.

Tuition

Lectures, exercises, labs and projects.

Specific requirements

Linear Algebra 7.5 ECTS credits, Calculus II 7.5 ECTS credits, Mechanics II 7.5 ECTS credits and Control Theory 7.5 ECTS credits or corresponding. In addition Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

Examination

Laboration (LAB1), 1,5 ECTS credits, marks Pass (G)
Project (PRO1), 1,5 ECTS credits, marks 3, 4 or 5
Examination (TEN1), 4,5 ECTS credits, marks 3, 4 or 5

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Pass with distinction, Pass with credit, Pass, Fail