Autonomous systems such as robots already are part of our daily life. In contrast to these machines, humans an react appropriately to their counterparts. People can hear and interpret human speech, and interpret facial expressions of other people.
This thesis presents a system for automatic facial expression recognition with emotion mapping. The system is image-based and employs feature-based feature extraction. This thesis analyzes the common steps of an emotion recognition system and presents state-of-the-art methods. The approach presented is based on 2D features. These features are detected in the face. No neutral face is needed as reference. The system extracts two types of facial parameters. The first type consists of distances between the feature points. The second type comprises angles between lines connecting the feature points. Both types of parameters are implemented and tested. The parameters which provide the best results for expression recognition are used to compare the system with state-of-the-art approaches. A multiclass Support Vector Machine classifies the parameters.
The results are codes of Action Units of the Facial Action Coding System. These codes are mapped to a facial emotion. This thesis addresses the six basic emotions (happy, surprised, sad, fearful, angry, and disgusted) plus the neutral facial expression. The system presented is implemented in C++ and is provided with an interface to the Robot Operating System (ROS).
The purpose of this bachelor- thesis is to teach Lisa - a robot of the university of Koblenz- AGAS department developed for participation in the @home league of the RoboCup - to draw. This requires the expansion of the robbie software framework and the operation of the robot- hardware components. Under consideration of a possible entry in the Open Challenge of the @home RoboCup, the goals are to detect a sheet of paper using Lisa- visual sensor, a Microsoft Kinect and draw on it using her Neuronics Katana robot arm. In addition, a pen mounting for the arm- gripper has to be constructed.
Outlined within this thesis are the procedures utilized to convert an image template into movement of the robotic arm, which in turn leads to drawing of a painting by the pen attached to the arm on a piece of paper detected by the visual sensor through image processing. Achieved were the parsing and drawing of an object made up of an indefinite amount of straight lines from a SVG-file onto a white sheet of paper, detected on a slightly darker surface and surrounded by various background objects or textures.
Pedestrian Detection in digital images is a task of huge importance for the development of automaticsystems and in improving the interaction of computer systems with their environment. The challenges such a system has to overcome are the high variance of the pedestrians to be recognized and the unstructured environment. For this thesis, a complete system for pedestrian detection was implemented according to a state of the art technique. A novel insight about precomputing the Color Self-Similarity accelerates the computations by a factor of four. The complete detection system is described and evaluated, and was published under an open source license.
The goal of this Bachelor thesis was programming an existig six-legged robot, which should be able to explore any environment and create a map of it autonomous. A laser scanner is to be integrated for cognition of this environment. To build the map and locate the robot a suitable SLAM(Simultaneous Localization and Mapping) technique will be connected to the sensor data. The map is reported to be the robots base of path planning and obstancle avoiding, what will be developed in the scope of the bachelor thesis, too. Therefore both GMapping and Hector SLAM will be implemented and tested.
An exploration algorithm is described in this bachelor thesis for exploring the robots environment. The implementation on the robot takes place in the space of ROS(Robot Operating System) framework on a "Raspberry Pi" miniature PC.