Lectures
1. Subject instruction. Course review. Relation of the control theory with the need for sensors.
2. Sensor types for mechatronic and robotic systems, their typical applications. Communication and data acquisition, converters. ROS-based visualization and simulation of sensor data.
3. Proximity and displacement sensors: photoelectric (infrared), inductive, capacitive, ultrasound- and laser-based, other. Principles and limitations.
4. Rotary displacement sensors. Temperature sensors. Bend, pressure (force), torque sensors, strain gauges. Principles and limitations.
5. IMU sensors and principles behind accelerometer, gyroscope, magnetometer. Problematics of odometry.
6. Camera systems and lenses: RGB, infrared, thermal. Typical industrial tasks, applications in service robotics.
7. Optical flow, disparity map algorithms, visual odometry – algorithms, approaches and limitations.
8. Sensors for biomedical mechatronic systems. Principles: EMG, NIRS, Ultrasonography.
9. Range imaging – main approaches. Stereo triangulation sensors – specifics, principles, advantages and disadvantages, limitations and common applications.
10. Structured light sensors – specifics, principles, advantages and disadvantages, limitations and common applications.
11. Time-of-flight sensors, interferometry, coded aperture – specifics, principles, advantages and disadvantages, limitations and common applications.
12. Sensors for monitoring the production site.
13. Multi-sensor data fusion, filtering, processing. Introduction into problematics of navigation, SLAM.
Seminars:
1. Preparing working environment (ROS, Arduino IDE).
2. Preparing ROS-based visualization and simulation of sensor data.
3. Proximity and displacement sensors: photoelectric (infrared), inductive, capacitive, ultrasound- and laser-based, other.
4. Rotary displacement sensors. Temperature sensors. Bend, pressure (force), torque sensors, strain gauges.
5. Accelerometers, gyroscopes, IMU sensors. Implementing simple odometry and visualizing the data.
6. Camera systems: RGB, infrared, thermal.
7. Optical flow, disparity map algorithms, gesture recognition.
8. Visual odometry. Utilizing specialized sensor and implementing a solution using a standard RGB camera.
9. Sensors for biomedical systems.
10. Stereo triangulation sensors – data acquisition, processing, visualizing.
11. Utilizing depth camera simulation in V-Rep, Gazebo.
12. Structured light and time-of-flight sensors – data acquisition, processing, visualizing. Skeleton tracking.
13. Utilizing out-of-box solutions for image processing, knowledge test.
1. Subject instruction. Course review. Relation of the control theory with the need for sensors.
2. Sensor types for mechatronic and robotic systems, their typical applications. Communication and data acquisition, converters. ROS-based visualization and simulation of sensor data.
3. Proximity and displacement sensors: photoelectric (infrared), inductive, capacitive, ultrasound- and laser-based, other. Principles and limitations.
4. Rotary displacement sensors. Temperature sensors. Bend, pressure (force), torque sensors, strain gauges. Principles and limitations.
5. IMU sensors and principles behind accelerometer, gyroscope, magnetometer. Problematics of odometry.
6. Camera systems and lenses: RGB, infrared, thermal. Typical industrial tasks, applications in service robotics.
7. Optical flow, disparity map algorithms, visual odometry – algorithms, approaches and limitations.
8. Sensors for biomedical mechatronic systems. Principles: EMG, NIRS, Ultrasonography.
9. Range imaging – main approaches. Stereo triangulation sensors – specifics, principles, advantages and disadvantages, limitations and common applications.
10. Structured light sensors – specifics, principles, advantages and disadvantages, limitations and common applications.
11. Time-of-flight sensors, interferometry, coded aperture – specifics, principles, advantages and disadvantages, limitations and common applications.
12. Sensors for monitoring the production site.
13. Multi-sensor data fusion, filtering, processing. Introduction into problematics of navigation, SLAM.
Seminars:
1. Preparing working environment (ROS, Arduino IDE).
2. Preparing ROS-based visualization and simulation of sensor data.
3. Proximity and displacement sensors: photoelectric (infrared), inductive, capacitive, ultrasound- and laser-based, other.
4. Rotary displacement sensors. Temperature sensors. Bend, pressure (force), torque sensors, strain gauges.
5. Accelerometers, gyroscopes, IMU sensors. Implementing simple odometry and visualizing the data.
6. Camera systems: RGB, infrared, thermal.
7. Optical flow, disparity map algorithms, gesture recognition.
8. Visual odometry. Utilizing specialized sensor and implementing a solution using a standard RGB camera.
9. Sensors for biomedical systems.
10. Stereo triangulation sensors – data acquisition, processing, visualizing.
11. Utilizing depth camera simulation in V-Rep, Gazebo.
12. Structured light and time-of-flight sensors – data acquisition, processing, visualizing. Skeleton tracking.
13. Utilizing out-of-box solutions for image processing, knowledge test.