Map Matching Performance under Various Similarity Metrics for Heterogeneous Robot Teams

Aerial and ground robots have various advantages of usage in different missions. Aerial robots can move quickly and get a different sight of view of the area, but those vehicles cannot carry heavy payloads. On the other hand, unmanned ground vehicles (UGVs) are slow moving vehicles, since those can carry heavier payloads than unmanned aerial vehicles (UAVs). In this context, we investigate the performances of various Similarity Metrics to provide a common map for Heterogeneous Robot Team (HRT) in complex environments. Within the usage of Lidar Odometry and Octree Mapping technique, the local 3D maps of the environment are gathered.  In order to obtain a common map for HRT, informative theoretic similarity metrics are exploited. All types of these similarity metrics gave adequate as allowable simulation time and accurate results that can be used in different types of applications. For the heterogeneous multi robot team, those methods can be used to match different types of maps.

Application of Robot Formation Scheme for Screening Solar Energy in a Greenhouse

Many agricultural and especially greenhouse applications like plant inspection, data gathering, spraying and selective harvesting could be performed by robots. In this paper multiple nonholonomic robots are used in order to create a desired formation scheme for screening solar energy in a greenhouse through data gathering. The formation consists from a leader and a team member equipped with appropriate sensors. Each robot is dedicated to its mission in the greenhouse that is predefined by the requirements of the application. The feasibility of the proposed application includes experimental results with three unmanned ground vehicles (UGV).

Alternative Approach in Ground Vehicle Wake Analysis

In this paper an alternative visualisation approach of the wake behind different vehicle body shapes with simplified and fully-detailed underbody has been proposed and analysed. This allows for a more clear distinction among the different wake regions. This visualisation is based on a transformation of the cartesian coordinates of a chosen wake plane to polar coordinates, using as filter velocities lower than the freestream. This transformation produces a polar wake plot that enables the division and quantification of the wake in a number of sections. In this paper, local drag has been used to visualise the drag contribution of the flow by the different sections. Visually, a balanced wake can be observed by the concentric behaviour of the polar plots. Alternatively, integration of the local drag of each degree section as a ratio of the total local drag yields a quantifiable approach of the wake uniformity, where different sections contribute equally to the local drag, with the exception of the wheels.