We develop computer vision methods for robot systems such as micro aerial vehicles and wheeled robots. In recent years, flying robots such as quadrocopters have gained increased interest in robotics and computer vision research. To navigate safely, these robots need the ability to localize themselves autonomously using their onboard sensors.
Real-Time Trajectory Replanning for MAVs
Real-time approach to local trajectory replanning for microaerial vehicles (MAVs). Current trajectory generation methods for multicopters achieve high success rates in cluttered environments, but assume that the environment is static and require prior knowledge of the map. In the presented study, we use the results of such planners and extend them with a local replanning algorithm that can handle unmodeled (possibly dynamic) obstacles while keeping the MAV close to the global trajectory.