Alpen, Mirco

This paper presents a criterion and control scheme based on the assumption of a bound on the gradient of a field distribution which guarantees to find the global extremum of the distribution. Mobile robots move through the search space gathering information at points which are calculated as a minimization problem over part of the search space which is guaranteed to include the global extremum based on the previously gathered measurements. Position control in combination with collision avoidance drives each robot to the next position while communicating its position to the other robots. Upon arrival, the next measurement of the field distribution is performed and the next position reference is calculated by each robot until the robots narrowed the search area to a single location. Previously proposed control schemes can find single points as candidates for the global maximum but struggle to guarantee that this point is the global extremum. Simulation results with robot models show the performance in comparison to a naive approach.

In this work, an approach for autonomous exploration and mapping of unknown indoor environments by a flying robot is presented. The used innovative SLAM algorithm (Simultaneous Localization And Mapping) works in real time and is based on the assumption of a predominant rectangular environment. The basic idea of SLAM is to merge several optical measurements collected by the robot at different positions and points of time. The global map is combined of the single measurements previously converted to local maps in each case. A key feature of the presented algorithm is the integration of a new measurement in the current global map within one step of iteration. The used flight platform is an industrial quadrotor that has been enhanced by the self-designed payload named ICAM (Intelligent Control And Measurement Unit) to realize the autonomous flight operations. Due to this, all needed algorithms for mapping and navigation can be implemented on board the flight robot and connection to a ground station during the mission is not required. The results show that the autonomous exploration and mapping of unknown indoor environments by a flying robot is possible.