Abstract The focus of this work is on extending the functionality of the robot platform Loomo. Using cartography and navigation methods, the basis for an autonomous system is created. In addition, the recognition and storage of AR markers simplifies human-robot interaction by enabling targeted navigation to specific locations. The implementation of the used software components ROS, Movebase, RTAB-Map and ALVAR is described in detail and tested in an experimental setting.
Abstract The demand among the population for household robots continues to rise. These include in particular mobile cleaning and lawn mowing robots. These are usually very expensive and still very inefficient. Especially for lawn mowing robots, it is essential to have visited the entire working space in order to perform their task correctly. However, the current state of the art is still random walk algorithms, which are very unreliable and inefficient.
Low cost robots, such as vacuum cleaners or lawn mowers employ simplistic and often random navigation policies. Although a large number of sophisticated mapping and planning approaches exist, they require additional sensors like LIDAR sensors, …