The aim of the thesis is to design, create and evaluate a user interface for control of service robot. I will focus on controlling of robotic arm, to be able to accomplish pick and place tasks. Specifically I will work with robotic platform PR2. The thesis describes different devices for sensing and perception of a user and usage of information from these devices to control robotic arm. Moreover, different methods for controlling of robotic arm are described there. Application design and implementation is presented further in this thesis together with description of the experiments used for evaluation of application.

Service robots need to be aware of persons in their vicinity in order to interact with them. People tracking enables the robot to perceive persons by fusing the information of several sensors. Most robots rely on laser range scanners and RGB cameras for this task. The thesis focuses on the detection and tracking of heads. This allows the robot to establish eye contact, which makes interactions feel more natural. Developing a fast and reliable pose-invariant head detector is challenging. The head detector that is proposed in this thesis works well on frontal heads, but is not fully pose-invariant. This thesis further explores adaptive tracking to keep track of heads that do not face the robot. Finally, head detector and adaptive tracker are combined within a new people tracking framework and experiments show its effectiveness compared to a state-of-the-art system.