Robotic Sensing, Perception, and Actuation

Course Description

Types and characteristics of sensors and actuators in robotics. Proprioceptive sensors (GPS, AHRS / IMU, DVL, force and torque, encoders). Perceptual sensors (cameras and somatosensory systems, lasers, sonars). Sensor fusion. Centralized and decentralized fusion mode. Smart environments and robot integration into smart environments. Visual feedback. Ways to control robotic actuators based on visual feedback

Learning Outcomes

  1. Learn and understand the characteristics of sensors and actuators used in robotics.
  2. Implement methods for acquiring and processing signals from sensors.
  3. Apply Kalman and information filters in processing signals from sensors.
  4. Know the principles of centralized and decentralized sensor fusion.
  5. aster the concept of smart environment and robot inclusion in smart environment.
  6. Control a robot based on the use of visual feedback

Forms of Teaching

Lectures

School board, Power Point presentation, practical demonstrations

Laboratory

Five laboratory exercises

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 100 % 20 % 100 % 20 %
Mid Term Exam: Written 50 % 40 % 50 %
Final Exam: Written 50 % 40 %

Week by Week Schedule

  1. GPS, AHRS (IMU); DVL
  2. Force and torque
  3. Encoders and other sensors
  4. Camera and somatosensory system
  5. Laser, Sonar
  6. Kalman and information filter
  7. Centralized sensor fusion, Decentralized sensor fusion
  8. Midterm exam
  9. End-point open-loop control, End-point closed-loop control
  10. Image based visual servoing
  11. DC motor, Servos
  12. Stepper and linear motors
  13. Biological background, Artifical muscle; Properties
  14. Artifical muscle technologies, McKibben muscle
  15. Final exam

Study Programmes

University graduate
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Free Elective Courses (2. semester)
Communication and Space Technologies (profile)
Free Elective Courses (2. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (2. semester)
Computer Engineering (profile)
Free Elective Courses (2. semester)
Computer Science (profile)
Free Elective Courses (2. semester)
Control Systems and Robotics (profile)
Core-elective Courses (2. semester)
Data Science (profile)
Free Elective Courses (2. semester)
Electrical Power Engineering (profile)
Free Elective Courses (2. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (2. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (2. semester)
Electronics (profile)
Free Elective Courses (2. semester)
Information and Communication Engineering (profile)
Free Elective Courses (2. semester)
Network Science (profile)
Free Elective Courses (2. semester)
Software Engineering and Information Systems (profile)
Free Elective Courses (2. semester)

Literature

(.), Clarence W. de Silva, Sensors and actuators - control systems instrumentation, CRC Press, 2007.,
(.), Peter Corke, Robotics, Vision and Control - Fundamental Algorithms in MATLAB®, Springer-Verlag Berlin Heidelberg, 2011.,
(.), Ernst D. Dyckmans, Dynamic Vision for Perception and Control of Motion, Springer-Verlag London, 2007.,
(.), Ming Xie, Fundamentals of Robotics - Linking Perception to Action, World Scientific Publishing Company, 2003.,

For students

General

ID 222656
  Summer semester
5 ECTS
L3 English Level
L3 e-Learning
45 Lectures
10 Laboratory exercises

Grading System

87,5 Excellent
75 Very Good
62,5 Good
50 Acceptable