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.
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, …
Abstract To make it easier for people to work in the lawn care, there is a long list of robotic lawnmowers. The navigation is a big problem, since the application is usually limited by a perimeter wire. This process means a time as well as financial expense and must be changed. For this purpose, a new method for lawn detection was developed at the Institute of Robotics and Cognitive Systems.