Tobias Naegeli

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This article describes an investigation of local motion planning, or collision avoidance, for a set of decisionmaking agents navigating in 3D space. The method is applicable to agents which are heterogeneous in size, dynamics and aggressiveness. It builds on the concept of velocity obstacles (VO),which characterizes the set of trajectories that lead to a(More)
Some aerial tasks are achieved more efficiently and at a lower cost by a group of independently controlled micro aerial vehicles (MAVs) when compared to a single, more sophisticated robot. Controlling formation flight can be cast as a two-level problem: stabilization of relative distances of agents (formation shape control) and control of the center of(More)
We propose a novel monocular visual inertial odometry algorithm that combines the advantages of EKF-based approaches with those of direct photometric error minimization methods. The method is based on sparse, very small patches and incorporates the minimization of photometric error directly into the EKF measurement model so that inertial data and(More)
We present a tracking system based on ultra-wideband (UWB) radio tranceivers mounted on a robot and a target. In comparison to typical UWB localization systems with fixed UWB tranceivers in the environment we only require instrumentation of the target with a single UWB tranceiver. Our system works in GPS-denied environments and does not suffer from(More)
The multi-robot path planning problem has been extensively studied for the cases of flying and driving vehicles. However, path planning for the case of vehicles that can both fly and drive has not yet been considered. Driving robots, while stable and energy efficient, are limited to mostly flat terrain. Quadcopters, on the other hand, are agile and highly(More)