TY  - JOUR
A1  - Gageik, Nils
A1  - Benz, Paul
A1  - Montenegro, Sergio
T1  - Obstacle Detection and Collision Avoidance for a UAV with Complementary Low-Cost Sensors
JF  - IEEE Access
N2  - This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.
KW  - infrared
KW  - collision avoidance
KW  - autonomous
KW  - UAV
KW  - quadrocopter
KW  - obstacle detection
KW  - quadrotor
KW  - distance measurement
KW  - ultrasonic autonomous aerial vehicles
KW  - helicopters
KW  - infrared detectors
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-125481
N1  - (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
VL  - 3
ER  - 
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  -