scholarly journals Photometric Long-Range Positioning of LED Targets for Cooperative Navigation in UAVs

Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 69
Author(s):  
Laurent Jospin ◽  
Alexis Stoven-Dubois ◽  
Davide Antonio Cucci
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Line Of Sight ◽  
Formation Model ◽  
Positioning Accuracy ◽  
Light Emitting ◽  
Cooperative Navigation ◽  
Area Of Interest ◽  
Multipath Effects ◽  
Photometric Error ◽  
Point Feature

Autonomous flight with unmanned aerial vehicles (UAVs) nowadays depends on the availability and reliability of Global Navigation Satellites Systems (GNSS). In cluttered outdoor scenarios, such as narrow gorges, or near tall artificial structures, such as bridges or dams, reduced sky visibility and multipath effects compromise the quality and the trustworthiness of the GNSS position fixes, making autonomous, or even manual, flight difficult and dangerous. To overcome this problem, cooperative navigation has been proposed: a second UAV flies away from any occluding objects and in line of sight from the first and provides the latter with positioning information, removing the need for full and reliable GNSS coverage in the area of interest. In this work we use high-power light-emitting diodes (LEDs) to signalize the second drone and we present a computer vision pipeline that allows to track the second drone in real-time from a distance up to 100 m and to compute its relative position with decimeter accuracy. This is based on an extension to the classical iterative algorithm for the Perspective-n-Points problem in which the photometric error is minimized according to a image formation model. This extension allow to substantially increase the accuracy of point-feature measurements in image space (up to 0.05 pixels), which directly translates into higher positioning accuracy with respect to conventional methods.

scholarly journals Cooperative navigation of unmanned aerial vehicle swarm based on cooperative dilution of precision

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142093271
Author(s):  
Mingxing Chen ◽  
Zhi Xiong ◽  
Jianye Liu ◽  
Rong Wang ◽  
Jun Xiong
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Influence Factors ◽  
Integrated Navigation ◽  
Positioning Accuracy ◽  
Position Information ◽  
Dilution Of Precision ◽  
Cooperative Navigation ◽  
Aerial Vehicles ◽  
Aerial Vehicle

Aiming at the formation problem in the cooperative navigation of unmanned aerial vehicle swarm, a cooperative position error analysis method based on cooperative dilution of precision is studied in this article. During cooperative flight, the unmanned aerial vehicle swarm can use the received position and ranging information of the adjacent unmanned aerial vehicles to calculate the position, and fuse with its own sensor position information. The final positioning accuracy depends not only on the capability of the ranging sensor but also on the position accuracy and formation of the adjacent unmanned aerial vehicles. In this article, these influence factors are combined to put forward a cooperative dilution of precision calculation method suitable for unmanned aerial vehicle swarm cooperative navigation. On this basis, a cooperative integrated navigation method based on ranging information is designed. Finally, the performance of cooperative navigation of unmanned aerial vehicles in different formations is simulated and analyzed. The simulation result shows that the cooperative dilution of precision method proposed in this article can effectively analyze the influence of formation on the positioning accuracy of unmanned aerial vehicle swarm, and the final combined positioning result is consistent with the cooperative dilution of precision analysis result.

Ultra-Wideband-Based Localization for Quadcopter Navigation

2016 ◽  
Vol 04 (01) ◽  
pp. 23-34 ◽  
Author(s):  
Kexin Guo ◽  
Zhirong Qiu ◽  
Cunxiao Miao ◽  
Abdul Hanif Zaini ◽  
Chun-Lin Chen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Positioning System ◽  
Localization Algorithm ◽  
Control Loop ◽  
Flight Tests ◽  
Localization System ◽  
Global Positioning

Micro unmanned aerial vehicles (UAVs) are promising to play more and more important roles in both civilian and military activities. Currently, the navigation of UAVs is critically dependent on the localization service provided by the Global Positioning System (GPS), which suffers from the multipath effect and blockage of line-of-sight, and fails to work in an indoor, forest or urban environment. In this paper, we establish a localization system for quadcopters based on ultra-wideband (UWB) range measurements. To achieve the localization, a UWB module is installed on the quadcopter to actively send ranging requests to some fixed UWB modules at known positions (anchors). Once a distance is obtained, it is calibrated first and then goes through outlier detection before being fed to a localization algorithm. The localization algorithm is initialized by trilateration and sustained by the extended Kalman filter (EKF). The position and velocity estimates produced by the algorithm will be further fed to the control loop to aid the navigation of the quadcopter. Various flight tests in different environments have been conducted to validate the performance of UWB ranging and localization algorithm.

A Localization Algorithm Research to Eliminate the Indoor NLOS Error

2014 ◽  
Vol 989-994 ◽  
pp. 2232-2236 ◽  
Author(s):  
Jia Zhi Dong ◽  
Yu Wen Wang ◽  
Feng Wei ◽  
Jiang Yu
Keyword(s):  
Indoor Environment ◽  
Arrival Time ◽  
Channel Model ◽  
Indoor Positioning ◽  
Superior Performance ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Positioning Accuracy ◽  
Software Simulation ◽  
Positioning Algorithm

Currently, there is an urgent need for indoor positioning technology. Considering the complexity of indoor environment, this paper proposes a new positioning algorithm (N-CHAN) via the analysis of the error of arrival time positioning (TOA) and the channels of S-V model. It overcomes an obvious shortcoming that the accuracy of traditional CHAN algorithm effected by no-line-of-sight (NLOS). Finally, though MATLAB software simulation, we prove that N-CHAN’s superior performance in NLOS in the S-V channel model, which has a positioning accuracy of centimeter-level and can effectively eliminate the influence of NLOS error on positioning accuracy. Moreover, the N-CHAN can effectively improve the positioning accuracy of the system, especially in the conditions of larger NLOS error.

scholarly journals Application of a WiFi/Geomagnetic Combined Positioning Method in a Single Access Point Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hongbin Pan ◽  
Yang Xiang ◽  
Jian Xiong ◽  
Yifan Zhao ◽  
Ziwei Huang ◽  
...  
Keyword(s):  
Nearest Neighbor ◽  
Detection Method ◽  
Access Point ◽  
Combination Method ◽  
Data Set ◽  
Positioning Accuracy ◽  
Multipath Effects ◽  
Positioning Method ◽  
Fingerprint Database ◽  
Mismatch Rate

Because of the particularity of urban underground pipe corridor environment, the distribution of wireless access points is sparse. It causes great interference to a single WiFi positioning method or geomagnetic method. In order to meet the positioning needs of daily inspection staff, this paper proposes a WiFi/geomagnetic combined positioning method. In this combination method, firstly, the collected WiFi strength data was filtered by outlier detection method. Then, the filtered data set was used to construct the offline fingerprint database. In the following positioning operation, the classical k -nearest neighbor algorithm was firstly used for preliminary positioning. Then, a standard circle was constructed based on the points obtained by the algorithm and the actual coordinate points. The diameter of the standard circle was the error, and the geomagnetic data were used for more accurate positioning in this circle. The method reduced the WiFi mismatch rate caused by multipath effects and improved positioning accuracy. Finally, a positioning accuracy experiment was performed in a single AP distribution environment that simulates a pipe corridor environment. The results proves that the WiFi/geomagnetic combined positioning method proposed in this paper is superior to the traditional WiFi and geomagnetic positioning methods in terms of positioning accuracy.

A survey on stereo vision-based autonomous navigation for multi-rotor MUAVs

Robotica ◽  
2018 ◽  
Vol 36 (8) ◽  
pp. 1225-1243 ◽  
Author(s):  
Jose-Pablo Sanchez-Rodriguez ◽  
Alejandro Aceves-Lopez
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Stereo Vision ◽  
Autonomous Navigation ◽  
Three Dimensional ◽  
Field Of View ◽  
Line Of Sight ◽  
Onboard Computer ◽  
Low Weight ◽  
Vision Based Navigation ◽  
Difficult Challenge

SUMMARYThis paper presents an overview of the most recent vision-based multi-rotor micro unmanned aerial vehicles (MUAVs) intended for autonomous navigation using a stereoscopic camera. Drone operation is difficult because pilots need the expertise to fly the drones. Pilots have a limited field of view, and unfortunate situations, such as loss of line of sight or collision with objects such as wires and branches, can happen. Autonomous navigation is an even more difficult challenge than remote control navigation because the drones must make decisions on their own in real time and simultaneously build maps of their surroundings if none is available. Moreover, MUAVs are limited in terms of useful payload capability and energy consumption. Therefore, a drone must be equipped with small sensors, and it must carry low weight. In addition, a drone requires a sufficiently powerful onboard computer so that it can understand its surroundings and navigate accordingly to achieve its goal safely. A stereoscopic camera is considered a suitable sensor because of its three-dimensional (3D) capabilities. Hence, a drone can perform vision-based navigation through object recognition and self-localise inside a map if one is available; otherwise, its autonomous navigation creates a simultaneous localisation and mapping problem.

A simple design of uniform LED illumination using catadioptric collimator and freeform lenslet array

2021 ◽  
pp. 147715352110524
Author(s):  
DT Vu ◽  
H Vu ◽  
S Shin ◽  
NM Kieu ◽  
TQ Tien ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Light Emitting Diode ◽  
Optical Path Length ◽  
Light Emitting ◽  
Simple Strategy ◽  
Area Of Interest ◽  
Lenslet Array ◽  
Freeform Optics ◽  
Receiver Plane ◽  
Indoor Lighting

We introduce a compact lenslet array principle that takes advantage of freeform optics to deploy a light distributor, beneficial for highly efficient, inexpensive, low energy consumption light-emitting diode (LED) lighting system. We outline here a simple strategy for designing the freeform lens that makes use of an array of the identical plano-convex lenslet. The light is redistributed from such lenslet, hinging on the principle of optical path length conservation, and then delivered to the receiver plane. The superimposing of such illumination area from every lenslet occurs on the receiver plane, in which the non-uniform illumination area located in the boundary should have the same dimension as the size of the freeform lenslet array. Such an area, insofar, is negligible due to their small size, which is the crux of our design, representing a large departure from the former implementations. Based on simulations that assess light performance, the proposed design exhibited the compatibility for multiple radiation geometries and off-axis lighting without concern for the initial radiation pattern of the source. As simulated, the LED light source integrated with such proposed freeform lenslet array revealed high luminous efficiency and uniformity within the illumination area of interest were above 70% and 85%, respectively. Such novel design was then experimentally demonstrated to possess a uniformity of 75% at hand, which was close to the simulation results. Also, proposed indoor lighting was implemented in comparison with the commercial LED downlight and LED panel, whereby the energy consumption, number of luminaires and illumination performance were assessed to show the advantage of our simplified model.

scholarly journals Base Station Selection for Hybrid TDOA/RTT/DOA Positioning in Mixed LOS/NLOS Environment

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4132
Author(s):  
Zhongliang Deng ◽  
Hanhua Wang ◽  
Xinyu Zheng ◽  
Lu Yin
Keyword(s):  
Selection Method ◽  
Base Station ◽  
Line Of Sight ◽  
Positioning Accuracy ◽  
Channel Condition ◽  
Fifth Generation ◽  
Hybrid Positioning ◽  
Channel Conditions ◽  
Geometric Dilution Of Precision ◽  
Value Changes

The fifth generation (5G) cellular communication system is designed to support Time Difference of Arrival (TDOA), Round-Trip Time (RTT), and Direction of Arrival (DOA) measurements for indoor positioning. To mitigate the positioning error caused by non-line-of-sight (NLOS), existing base station selection methods identify channel conditions and only use line-of-sight (LOS) signals for positioning. However, different selected base station combination would lead to a different geometric dilution of precision (GDOP), base station selection based only on channel condition is not fully applicable for the hybrid positioning. This paper derives the GDOP for the hybrid TDOA, RTT, and DOA positioning, and proposes a GDOP-assisted base station selection method, which is based on both channel conditions and GDOP value changes. The simulation shows that using the proposed base station selection method could lead to higher positioning accuracy than base station selection based only on channel condition. In the simulation, in the side region of the scenario, where the change of selected base station combination causes a notable increment in GDOP value, the positioning accuracy improvement caused by the proposed method is greater than that in the center region.

scholarly journals Collective Perception Using UAVs: Autonomous Aerial Reconnaissance in a Complex Urban Environment

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2926
Author(s):  
Petr Stodola ◽  
Jan Drozd ◽  
Karel Šilinger ◽  
Jan Hodický ◽  
Dalibor Procházka
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Urban Environment ◽  
Computer Simulations ◽  
Optimal Solutions ◽  
Uneven Terrain ◽  
Area Of Interest ◽  
Aerial Vehicles ◽  
Benchmark Instances ◽  
Aerial Reconnaissance

This article examines autonomous reconnaissance in a complex urban environment using unmanned aerial vehicles (UAVs). Environments with many buildings and other types of obstacles and/or an uneven terrain are harder to be explored as occlusion of objects of interest may often occur. First, in this article, the problem of autonomous reconnaissance in a complex urban environment via a swarm of UAVs is formulated. Then, the algorithm based on the metaheuristic approach is proposed for a solution. This solution lies in deploying a number of waypoints in the area of interest to be explored, from which the monitoring is performed, and planning the routes for available UAVs among these waypoints so that the monitored area is as large as possible and the operation as short as possible. In the last part of this article, two types of main experiments based on computer simulations are designed to verify the proposed algorithms. The first type focuses on comparing the results achieved on the benchmark instances with the optimal solutions. The second one presents and discusses the results obtained from a number of scenarios, which are based on typical reconnaissance operations in real environments.

scholarly journals Passive Visible Light Detection of Humans

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1902 ◽  
Author(s):  
Kenneth Deprez ◽  
Sander Bastiaens ◽  
Luc Martens ◽  
Wout Joseph ◽  
David Plets
Keyword(s):  
Visible Light ◽  
Detection Rate ◽  
Detection System ◽  
Light Emitting Diode ◽  
Line Of Sight ◽  
Controlled Environment ◽  
Ambient Light ◽  
Light Emitting ◽  
Light Sensing ◽  
Reflected Light

This paper experimentally investigates passive human visible light sensing (VLS). A passive VLS system is tested consisting of one light emitting diode (LED) and one photodiode-based receiver, both ceiling-mounted. There is no line of sight between the LED and the receiver, so only reflected light can be considered. The influence of a human is investigated based on the received signal strength (RSS) values of the reflections of ambient light at the photodiode. Depending on the situation, this influence can reach up to ± 50 % . The experimental results show the influence of three various clothing colors, four different walking directions and four different layouts. Based on the obtained results, a human pass-by detection system is proposed and tested. The system achieves a detection rate of 100% in a controlled environment for 21 experiments. For a realistic corridor experiment, the system keeps its detection rate of 100% for 19 experiments.

scholarly journals A time difference of arrival/angle of arrival fusion algorithm with steepest descent algorithm for indoor non-line-of-sight locationing

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771986035 ◽  
Author(s):  
Chong Shen ◽  
Chengxiao Wang ◽  
Kun Zhang ◽  
Xianpeng Wang ◽  
Jing Liu
Keyword(s):  
Steepest Descent ◽  
Time Difference ◽  
Line Of Sight ◽  
Angle Of Arrival ◽  
Fusion Algorithm ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Descent Algorithm ◽  
Steepest Descent Algorithm ◽  
Non Line Of Sight

In complex indoor propagation environment, the non-line-of-sight error caused by various obstacles brings great error to node positioning. Choosing the appropriate signal transmission methods is important to improve node indoor positioning accuracy. In this research, ultra-wideband technology, as baseband with high theoretical positioning accuracy and real-time performance, is implemented to transmit indoor signals. The proposed fusion algorithm with ultra-wideband baseband takes advantages from both time difference of arrival and angle of arrival algorithms, combined through the steepest descent algorithm. The non-line-of-sight signal estimation error is iteratively eliminated to achieve effective positioning accuracy. The experimental results indicate that the novel time difference of arrival/angle of arrival fusion algorithm with steepest descent algorithm can largely improve node positioning accuracy and stability.

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