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This report presents an approach on a quadrotor dynamics stabilization based on ICP SLAM. Because the quadrotor lacks sensory information to detect its horizontal drift an additional sensor as Hokuyo-UTM has been used to perform on-line ICP-based SLAM. The obtained position estimates were used in control loops to maintain desired position and orientation of the vehicle. Such attitude parameters as height, yaw and position in space were controlled based on the laser data. As a result the quadrotor demonstrated two significant for autonomous navigation capabilities: performance of on-line SLAMon a flying vehicle and maintaining desired position in 3D space. Visual approach on optical flow based on Pyramid Lucas-Kanade algorithm has been touched and tested in different environmental conditions though hasn't been implemented in the control loop. Also the performance of the Hokuyo laser scanner and the related to it ICP SLAM algorithm have been tested in different environmental conditions indoors, outdoors and in presence of smoke. Results are presented and discussed. The requirement of performing on-line SLAM algorithm and to carry quite heavy equipment for it forced to seek a solution to increase the payload of the quadrotor with its computational power. A new hardware and distributed software architectures are therefore presented in the report.
Robots integrated into a social environment with humans need the ability to locate persons in their surrounding area. This is also the case for the WelcomeBot which is developed at the Fraunhofer Institute IAIS. In the future, the robot should follow persons in the buildings and guide them to certain areas. Therefore, it needs the capability to detect and track a person in the environment. In this master thesis, an approach for fast and reliable tracking of a person via a mobile robotic platform is presented. Based on the investigation of different methods and sensors, a laser scanner and a camera are selected as the primary two sensors.