scholarly journals Visual-Based Positioning of Aerial Maintenance Platforms on Overhead Transmission Lines

2019 ◽  
Vol 9 (1) ◽  
pp. 165 ◽  
Author(s):  
Oswaldo Menéndez ◽  
Marcelo Pérez ◽  
Fernando Auat Cheein
Keyword(s):  
Transmission Lines ◽  
Tracking System ◽  
Geometric Approach ◽  
Measurement Unit ◽  
Accurate Estimation ◽  
Morphological Operations ◽  
Image Processing Algorithm ◽  
Position Information ◽  
Promising Alternative ◽  
Transmission Grid

Unmanned aerial vehicles (UAVs) are an emerging and promising alternative for monitoring of transmission lines in terms of flexibility, complexity, working speed, and cost. One of the main challenges is to enable UAVs to become as autonomous as possible. A vital component toward this direction is the robust and accurate estimation of the UAV placement with respect to the transmission grid. This work faces this challenge by developing a transmission line autonomous tracking system, which allows the placement of a commercial drone over a transmission grid using a monocular camera. This feature provides accurate positioning for the vehicle even where the Global navigation satellite system (GNSS) signal is denied, enabling to report the status of transmission lines, at any time. The system isolates transmission grid conductors in each acquired RGB-image using an image-processing algorithm based on Hough transform, morphological operations, and Gabor filters. With this information, the system computes the location of the UAV using a geometric approach that relates transmission lines building parameter and optical geometry. However, it has the problem of gradual error accumulation when the drone moves. In this regards, the estimated position of the drone is computed by the maximum likelihood estimation (MLE) by the position information estimated by visual-system, the inertial measurement unit (IMU) and GNSS. The proposed positioning system showed an efficiency of 91.44% in field experimentation in the extraction of transmission conductor, with a root mean square the error of 0.18 m in the UAV localization.

scholarly journals Multi-sensor three-dimensional Monte Carlo localization for long-term aerial robot navigation

2017 ◽  
Vol 14 (5) ◽  
pp. 172988141773275 ◽  
Author(s):  
Francisco J Perez-Grau ◽  
Fernando Caballero ◽  
Antidio Viguria ◽  
Anibal Ollero
Keyword(s):  
Monte Carlo ◽  
Motion Tracking ◽  
Robot Navigation ◽  
Tracking System ◽  
Three Dimensional ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Localization Algorithm ◽  
Monte Carlo Localization ◽  
Motion Tracking System

This article presents an enhanced version of the Monte Carlo localization algorithm, commonly used for robot navigation in indoor environments, which is suitable for aerial robots moving in a three-dimentional environment and makes use of a combination of measurements from an Red,Green,Blue-Depth (RGB-D) sensor, distances to several radio-tags placed in the environment, and an inertial measurement unit. The approach is demonstrated with an unmanned aerial vehicle flying for 10 min indoors and validated with a very precise motion tracking system. The approach has been implemented using the robot operating system framework and works smoothly on a regular i7 computer, leaving plenty of computational capacity for other navigation tasks such as motion planning or control.

IoT Based Bus Tracking System

2021 ◽  
Vol 9 (VI) ◽  
pp. 2889-2893
Author(s):  
Miss Payal W. Paratpure
Keyword(s):  
Tracking System ◽  
Cost Effective ◽  
Raspberry Pi ◽  
Accurate Estimation ◽  
Time Of Arrival ◽  
Test Results ◽  
Cloud Server ◽  
Bus Operator ◽  
Gps Device

Tracking of public bus location requires a GPS device to be installed, and lots of bus operators in developing countries don't have such an answer in situ to supply an accurate estimation of bus time of arrival (ETA). Without ETA information, it's very difficult for the overall public to plan their journey effectively. In this paper, implementation of an innovative IOT solution to trace the real time location of buses without requiring the deployment of a GPS device is discussed. It uses Bluetooth Low Energy (BLE) proximity beacon to trace the journey of a bus by deploying an Estimate location beacon on the bus. BLE detection devices (Raspberry Pi 4) are installed at selected bus stops along the path to detect the arrival of buses. Once detected, the situation of the bus is submitted to a cloud server to compute the bus ETAs. A field trial is currently being conducted in Johor, Malaysia together with an area bus operator on one single path. Our test results showed that the detection of BLE beacons is extremely accurate and it's feasible to trace the situation of buses without employing a GPS device during a cost-effective way.

scholarly journals Integration of GPS, Monocular Vision, and High Definition (HD) Map for Accurate Vehicle Localization

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3270 ◽  
Author(s):  
Hao Cai ◽  
Zhaozheng Hu ◽  
Gang Huang ◽  
Dunyao Zhu ◽  
Xiaocong Su
Keyword(s):  
Kalman Filter ◽  
Low Cost ◽  
Kinematic Model ◽  
Intelligent Vehicles ◽  
Monocular Vision ◽  
Measurement Unit ◽  
High Definition ◽  
Position Information ◽  
Vehicle Localization ◽  
Lateral Distance

Self-localization is a crucial task for intelligent vehicles. Existing localization methods usually require high-cost IMU (Inertial Measurement Unit) or expensive LiDAR sensors (e.g., Velodyne HDL-64E). In this paper, we propose a low-cost yet accurate localization solution by using a custom-level GPS receiver and a low-cost camera with the support of HD map. Unlike existing HD map-based methods, which usually requires unique landmarks within the sensed range, the proposed method utilizes common lane lines for vehicle localization by using Kalman filter to fuse the GPS, monocular vision, and HD map for more accurate vehicle localization. In the Kalman filter framework, the observations consist of two parts. One is the raw GPS coordinate. The other is the lateral distance between the vehicle and the lane, which is computed from the monocular camera. The HD map plays the role of providing reference position information and correlating the local lateral distance from the vision and the GPS coordinates so as to formulate a linear Kalman filter. In the prediction step, we propose using a data-driven motion model rather than a Kinematic model, which is more adaptive and flexible. The proposed method has been tested with both simulation data and real data collected in the field. The results demonstrate that the localization errors from the proposed method are less than half or even one-third of the original GPS positioning errors by using low cost sensors with HD map support. Experimental results also demonstrate that the integration of the proposed method into existing ones can greatly enhance the localization results.

scholarly journals Assessment of Water Pumping System Powered By Solar Pump in Dry Areas

2019 ◽  
Vol 8 (4) ◽  
pp. 2859-2866
Keyword(s):  
Irrigation Water ◽  
Water Requirement ◽  
Accurate Estimation ◽  
Irrigation Water Requirement ◽  
Irrigation Planning ◽  
Power Requirement ◽  
Promising Alternative ◽  
Point Tracking ◽  
Water Pumping ◽  
Dry Areas

The rapid increase of desertification’s degradation is one of the worst environmental and economic threats for dry areas. Climate changes, very year impacts thousands of areas across the globe. The high cost of electricity and diesel-based fuel affects photovoltaic water pumping requirements for irrigation in many parts of the world. Solar irradiance in every dry place is extremely high due the drought increase. Thus, using solar energy for water pumping is a promising alternative sources of energy. Undertaking irrigation for a particular place and crop requires not only skills in the irrigation planning but also in the power requirement of the entire system. A reliable and accurate estimation of ET rate and irrigation water requirement (IWR) are soundly important in irrigation field. This sought to accurately estimate the irrigation power requirement by using PVsyst software on nine different pumps technologies combinations with different type of converters at 100m, 150m, 180m, and 200m of Total dynamic Head (TDH). The study has been conducted in four sections, the first section dealt with the assessment of the collected data, the second section with the simulations, the third one with the irrigation water requirement and finally irrigation water requirement. The results found in study show that IPR of a crop is majorly depend on the TDH. Among the nine combinations, results show that the Maximum Power Point Tracking (MPPT) technology is the best in terms of power requirement of selected the crop. Furthermore, the maximum and minimum values of the irrigation water requirement for millet crop was found to be 12.9 mm/day and 4.9mm/day respectively.

scholarly journals A Low-Cost Motion Capture System for Small-Scale Wave Energy Device Tank Testing

2018 ◽  
Vol 141 (3) ◽  
Author(s):  
Francesco Paparella ◽  
Satja Sivcev ◽  
Daniel Toal ◽  
John V. Ringwood
Keyword(s):  
Wave Energy ◽  
Motion Tracking ◽  
Tracking System ◽  
Low Cost ◽  
Measurement Unit ◽  
Small Scale ◽  
Energy Device ◽  
Optical Motion ◽  
Optical Motion Tracking ◽  
Motion Tracking System

The measurement of the motion of a small-scale wave energy device during wave tank tests is important for the evaluation of its response to waves and the assessment of power production. Usually, the motion of a small-scale wave energy converter (WEC) is measured using an optical motion tracking system with high precision and sampling rate. However, the cost for an optical motion tracking system can be considerably high and, therefore, the overall cost for tank testing is increased. This paper proposes a low-cost capture system composed of an inertial measurement unit and ultrasound sensors. The measurements from the ultrasound sensors are combined optimally with the measurements from the inertial measurement unit through an extended Kalman filter (EKF) in order to obtain an accurate estimation of the motion of a WEC.

Development and Experimental Verification of a Person Tracking System of Mobile Robots Using Sensor Fusion of Inertial Measurement Unit and Laser Range Finder for Occlusion Avoidance

2021 ◽  
Vol 33 (1) ◽  
pp. 33-43
Author(s):  
Kazuhiro Funato ◽  
Ryosuke Tasaki ◽  
Hiroto Sakurai ◽  
Kazuhiko Terashima ◽  
◽  
...  
Keyword(s):  
Mobile Robot ◽  
Sensor Fusion ◽  
Experimental Verification ◽  
Inertial Measurement Unit ◽  
Tracking System ◽  
Measurement Unit ◽  
Laser Range Finder ◽  
Range Finder ◽  
Inertial Measurement ◽  
Laser Range

The authors have been developing a mobile robot to assist doctors in hospitals in managing medical tools and patient electronic medical records. The robot tracks behind a mobile medical worker while maintaining a constant distance from the worker. However, it was difficult to detect objects in the sensor’s invisible region, called occlusion. In this study, we propose a sensor fusion method to estimate the position of a robot tracking target indirectly by an inertial measurement unit (IMU) in addition to the direct measurement by an laser range finder (LRF) and develop a human tracking system to avoid occlusion by a mobile robot. Based on this, we perform detailed experimental verification of tracking a specified person to verify the validity of the proposed method.

scholarly journals Obtaining World Coordinate Information of UAV in GNSS Denied Environments

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2241 ◽  
Author(s):  
Chengbin Chen ◽  
YaoYuan Tian ◽  
Liang Lin ◽  
SiFan Chen ◽  
HanWen Li ◽  
...  
Keyword(s):  
Visual Servoing ◽  
Field Tests ◽  
Visual Navigation ◽  
Sensor Data ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Complex Environments ◽  
External Interference ◽  
Position Information ◽  
Self Powered

GNSS information is vulnerable to external interference and causes failure when unmanned aerial vehicles (UAVs) are in a fully autonomous flight in complex environments such as high-rise parks and dense forests. This paper presents a pan-tilt-based visual servoing (PBVS) method for obtaining world coordinate information. The system is equipped with an inertial measurement unit (IMU), an air pressure sensor, a magnetometer, and a pan-tilt-zoom (PTZ) camera. In this paper, we explain the physical model and the application method of the PBVS system, which can be briefly summarized as follows. We track the operation target with a UAV carrying a camera and output the information about the UAV’s position and the angle between the PTZ and the anchor point. In this way, we can obtain the current absolute position information of the UAV with its absolute altitude collected by the height sensing unit and absolute geographic coordinate information and altitude information of the tracked target. We set up an actual UAV experimental environment. To meet the calculation requirements, some sensor data will be sent to the cloud through the network. Through the field tests, it can be concluded that the systematic deviation of the overall solution is less than the error of GNSS sensor equipment, and it can provide navigation coordinate information for the UAV in complex environments. Compared with traditional visual navigation systems, our scheme has the advantage of obtaining absolute, continuous, accurate, and efficient navigation information at a short distance (within 15 m from the target). This system can be used in scenarios that require autonomous cruise, such as self-powered inspections of UAVs, patrols in parks, etc.

An inertial measurement unit tracking system for body movement in comparison with optical tracking

2020 ◽  
Vol 234 (7) ◽  
pp. 728-737
Author(s):  
Rui Li ◽  
Barclay Jumet ◽  
Hongliang Ren ◽  
WenZhan Song ◽  
Zion Tsz Ho Tse
Keyword(s):  
Inertial Measurement Unit ◽  
Tracking System ◽  
Low Cost ◽  
Optical Tracking ◽  
Measurement Unit ◽  
Joint Movement ◽  
Joint Angles ◽  
Optical Tracking System ◽  
Microelectromechanical System ◽  
Inertial Measurement

The recent advancement of motion tracking technology offers better treatment tools for conditions, such as movement disorders, as the outcome of the rehabilitation could be quantitatively defined. The accurate and fast angular information output of the inertial measurement unit tracking systems enables the collection of accurate kinematic data for clinical assessment. This article presents a study of a low-cost microelectromechanical system inertial measurement unit-based tracking system in comparison with the conventional optical tracking system. The system consists of seven microelectromechanical system inertial measurement units, which could be mounted on the lower limbs of the subjects. For the feasibility test, 10 human participants were instructed to perform three different motions: walking, running, and fencing lunges when wearing specially designed sleeves. The subjects’ lower body movements were tracked using our inertial measurement unit-based system and compared with the gold standard—the NDI Polaris Vega optical tracking system. The results of the angular comparison between the inertial measurement unit and the NDI Polaris Vega optical tracking system were as follows: the average cross-correlation value was 0.85, the mean difference of joint angles was 2.00°, and the standard deviation of joint angles was ± 2.65°. The developed microelectromechanical system–based tracking system provides an alternative low-cost solution to track joint movement. Moreover, it is able to operate on an Android platform and could potentially be used to assist outdoor or home-based rehabilitation.

Optimized 3D laser point cloud reconstruction by gradient descent technique

2020 ◽  
Vol 47 (3) ◽  
pp. 409-421
Author(s):  
Ravinder Singh ◽  
Archana Khurana ◽  
Sunil Kumar
Keyword(s):  
Point Cloud ◽  
Time Synchronization ◽  
Laser Scanner ◽  
Mobile Robot Navigation ◽  
Measurement Unit ◽  
3D Point Cloud ◽  
Servo Motor ◽  
Position Information ◽  
Content Type ◽  
Aerial Navigation

Purpose This study aims to develop an optimized 3D laser point reconstruction using Descent Gradient algorithm. Precise and accurate reconstruction of 3D laser point cloud of the complex environment/object is a key solution for many industries such as construction, gaming, automobiles, aerial navigation, architecture and automation. A 2D laser scanner along with a servo motor/pan tilt/inertial measurement unit is used for generating 3D point cloud (either environment/object or both) by acquiring the real-time data from sensors. However, while generating the 3D laser point cloud, various problems related to time synchronization problem between laser and servomotor and torque variation in servomotors arise, which causes misalignment in stacking the 2D laser scan for generating the 3D point cloud of the environment. Because of the misalignment in stacking, the 2D laser scan corresponding to the erroneous angular and position information by the servomotor and the 3D laser point cloud become distorted in terms of inconsistency for measuring the dimension of the objects. Design/methodology/approach This paper addresses a modified 3D laser system assembled from a 2D laser scanner coupled with a servomotor (dynamixel motor) for developing an efficient 3D laser point cloud with the implementation of an optimization technique: descent gradient filter (DGT). The proposed approach reduces the cost function (error) in the angular and position coordinates of the servo motor caused because of torque variation and time synchronization, which resulted in enhancing the accuracy in 3D point cloud mapping for the accurate measurement of the object’s dimensions. Findings Various real-world experiments are performed with the proposed DGT filter linked with laser scanner and servomotor and an improvement of 6.5 per cent in measuring the accurate dimension of object is obtained while comparing with conventional approaches for generating a 3D laser point cloud. Originality/value This proposed technique may be applicable for various industrial applications that are based on robotics arms (such as painting, welding and cutting) in the automobile industry, the optimized measurement of object, efficient mobile robot navigation, precise 3D reconstruction of environment/object in construction, architecture applications, airborne applications and aerial navigation.

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