TY  - JOUR
A1  - Strohmeier, Michael
A1  - Walter, Thomas
A1  - Rothe, Julian
A1  - Montenegro, Sergio
T1  - Ultra-wideband based pose estimation for small unmanned aerial vehicles
JF  - IEEE Access
N2  - This paper proposes a 3-D local pose estimation system for a small Unmanned Aerial Vehicle (UAV) with a weight limit of 200 g and a very small footprint of 10 cm×10cm. The system is realized by fusing 3-D position estimations from an Ultra-Wide Band (UWB) transceiver network with Inertial Measurement Unit (IMU) sensor data and data from a barometric pressure sensor. The 3-D position from the UWB network is estimated using Multi-Dimensional Scaling (MDS) and range measurements between the transceivers. The range measurements are obtained using Double-Sided Two-Way Ranging (DS-TWR), thus eliminating the need for an additional clock synchronization mechanism. The sensor fusion is accomplished using a loosely coupled Extended Kalman Filter (EKF) architecture. Extensive evaluation of the proposed system shows that a position accuracy with a Root-Mean-Square Error (RMSE) of 0.20cm can be obtained. The orientation angle can be estimated with an RMSE of 1.93°.
KW  - UAV
KW  - navigation
KW  - pose estimation
KW  - distance measurement
KW  - DecaWave
KW  - extended Kalman filter
KW  - UWB
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-177503
VL  - 6
ER  - 
TY  - JOUR
A1  - Kaiser, Dennis
A1  - Lesch, Veronika
A1  - Rothe, Julian
A1  - Strohmeier, Michael
A1  - Spieß, Florian
A1  - Krupitzer, Christian
A1  - Montenegro, Sergio
A1  - Kounev, Samuel
T1  - Towards Self-Aware Multirotor Formations
JF  - Computers
N2  - In the present day, unmanned aerial vehicles become seemingly more popular every year, but, without regulation of the increasing number of these vehicles, the air space could become chaotic and uncontrollable. In this work, a framework is proposed to combine self-aware computing with multirotor formations to address this problem. The self-awareness is envisioned to improve the dynamic behavior of multirotors. The formation scheme that is implemented is called platooning, which arranges vehicles in a string behind the lead vehicle and is proposed to bring order into chaotic air space. Since multirotors define a general category of unmanned aerial vehicles, the focus of this thesis are quadcopters, platforms with four rotors. A modification for the LRA-M self-awareness loop is proposed and named Platooning Awareness. The implemented framework is able to offer two flight modes that enable waypoint following and the self-awareness module to find a path through scenarios, where obstacles are present on the way, onto a goal position. The evaluation of this work shows that the proposed framework is able to use self-awareness to learn about its environment, avoid obstacles, and can successfully move a platoon of drones through multiple scenarios.
KW  - self-aware computing
KW  - unmanned aerial vehicles
KW  - multirotors
KW  - quadcopters
KW  - intelligent transportation systems
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-200572
SN  - 2073-431X
VL  - 9
IS  - 1
ER  - 
TY  - JOUR
A1  - Werner, Lennart
A1  - Strohmeier, Michael
A1  - Rothe, Julian
A1  - Montenegro, Sergio
T1  - Thrust vector observation for force feedback-controlled UAVs
JF  - Drones
N2  - This paper presents a novel approach to Thrust Vector Control (TVC) for small Unmanned Aerial Vehicles (UAVs). The difficulties associated with conventional feed-forward TVC are outlined, and a practical solution to conquer these challenges is derived. The solution relies on observing boom deformations that are created by different thrust vector directions and high-velocity air inflow. The paper describes the required measurement electronics as well as the implementation of a dedicated testbed that allows the evaluation of mid-flight force measurements. Wind-tunnel tests show that the presented method for active thrust vector determination is able to quantify the disturbances due to the incoming air flow.
KW  - unmanned aerial vehicles
KW  - thrust vector control
KW  - force feedback
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-262153
SN  - 2504-446X
VL  - 6
IS  - 2
ER  -