Overview

Start: May 05, 2025
End: July 31, 2025

Lab Class Announcement SS 2025:

• Please click here

Objectives and Content:

• The Lab is coordinated with the lecture "Measurement and Control Systems". While the lecture is focusing on principles and sub-systems, the Lab focuses on measuring methods for the most important industrial measured variables.

Requirements:

• Knowledge of the lecture "Measurement and Control Systems

• Annotation:

  Each experiment begins with a 30-minute colloquium. It is checked whether you are familiar with the substance and the content of the experiment. You may only carry out the actual experiment if you have passed the colloquium. Thorough preparation of the respective experiment is a prerequisite for passing the colloquium.

Registration:

• Registration on this website from April 1st, 2025, 10:00 a.m. - April 20, 2025, midnight
• The Lab must also be registered as an examination in the CAS of the KIT!

Experiment instructions:

• Brief description of the experiments:
  • A1   Measurement of stochastic signals:
    This experiment is divided into 2 parts. In the first part, the acceleration of gravity is estimated from a series of observations. The gravitational acceleration is derived from the measured height of fall and the duration of the fall of a ball. In addition to the actual determination of the measured value (acceleration of gravity), a discussion of the measurement accuracy is essential, since without accuracy the measurement result has no meaningfulness.
    In part two, the Kalman filter is presented and explained using a clear example.
  • B1   Image recording and analysis:
    The C-series of experiments in this lab deals with measuring and processing signals in image form. In the first experiment, students will learn how to capture images with a camera. Subsequently, converting images into different formats and analyzing image properties will be taught. Statistical methods such as histograms will be used for the analysis, and various lighting parameters will be tested.
  • B2   Image Processing with filters and segmentation:
    The second experiment in the C-series focuses on various image processing techniques, such as filtering. Using different filters, edges of objects will be detected, and then a Hough transformation will be implemented to approximate shapes. Based on the detected edges and shapes, objects in the image can be segmented. For comparison, segmentation based on a color filter will also be implemented.
  • B3   3D Scene Understanding and Depth Estimation with a stereo camera:
    In the last part of the C-series, the topic of 3D scene understanding will be addressed. For this purpose, students will create a camera model for a stereo camera as a basis for depth estimation and analyze the positions of various objects in the space. Based on this depth estimation, a 3D grid will be generated, which reflects the scene in the camera image in 3D space.
  • C1   Object recognition with Deep Learning:
    In many areas of image processing, classical methods have been replaced or extended by learning methods. In this experiment, students will be introduced to neural networks, a technique from deep learning. For this purpose, an autonomous driving car will be extended with traffic sign recognition, so that this car drives a course based on traffic signs. For this traffic sign recognition, a neural network will be trained on a given dataset, and the driving behavior of the vehicle (e.g., collision avoidance) will be optimized.
  • D1   Control of an Industrial Robot:
    In experiment D1, the knowledge from image processing will be applied and extended with control. This is done using an overall system, in this case, an industrial robot arm. This robot arm has a table tennis racket mounted on the gripper, and the goal of this experiment is for the robot to juggle the ball using table tennis ball recognition and control. For this purpose, the system must be analyzed, and a discrete controller must be implemented and parameterized.
  • D2 and D3   Ball-Balancing Table:
    The series of experiments on the ball-balancing table is divided into two parts, each conducted on a separate experiment date. In an experimental setup consisting of a table that can be tilted in two directions by servo motors, control engineering fundamentals will be practically tested. The goal is to balance a ball on the table and follow various predefined paths. This will initially be achieved with a simple PID controller and a filter for the sensor measurements. Suitable filter and control parameters will be determined analytically and experimentally, and their influence on control behavior and control quality will be qualitatively and quantitatively evaluated. Finally, an outlook on control concepts beyond the basic lecture will be given.
• Detailed test instructions are available on this website from mid-April each year
• Guidelines and Routing slip

Dates and groups:

• Group division and experimental arrangement will be published here on April 28, 2025
• It is not possible to change groups during the semester!
• Room allocation (will be available here from mid-April on)

Dates:

Experiment1:         calendar week 19         05/05/25 - 08/05/25
Experiment2:         calendar week 20         12/05/25 - 15/05/25
Experiment3:         calendar week 21         19/05/25 - 22/05/25
Experiment4:         calendar week 23         02/06/25 - 05/06/25
Experiment5:         calendar week 27         30/06/25 - 03/07/25
Experiment6:         calendar week 28         07/07/25 - 10/07/25
Experiment7:         calendar week 29         14/07/25 - 17/07/25
Experiment8:         calendar week 30         21/07/25 - 24/07/25

Date for repeated experiments

                              calendar week 31         28/07/25 - 31/07/25

-> The Lab takes place during the semester. In each week, an experiment is carried out for the groups according to the group division.