scholarly journals Cooperative UAV–UGV Autonomous Power Pylon Inspection: An Investigation of Cooperative Outdoor Vehicle Positioning Architecture

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6384
Author(s):  
Alvaro Cantieri ◽  
Matheus Ferraz ◽  
Guido Szekir ◽  
Marco Antônio Teixeira ◽  
José Lima ◽  
...  
Keyword(s):  
Power Distribution ◽  
Autonomous Vehicles ◽  
Path Following ◽  
Obstacle Detection ◽  
Unmanned Aircraft ◽  
Position Information ◽  
Technical Problems ◽  
Inspection Process ◽  
Vehicle Positioning ◽  
Power Distribution Lines

Realizing autonomous inspection, such as that of power distribution lines, through unmanned aerial vehicle (UAV) systems is a key research domain in robotics. In particular, the use of autonomous and semi-autonomous vehicles to execute the tasks of an inspection process can enhance the efficacy and safety of the operation; however, many technical problems, such as those pertaining to the precise positioning and path following of the vehicles, robust obstacle detection, and intelligent control, must be addressed. In this study, an innovative architecture involving an unmanned aircraft vehicle (UAV) and an unmanned ground vehicle (UGV) was examined for detailed inspections of power lines. In the proposed strategy, each vehicle provides its position information to the other, which ensures a safe inspection process. The results of real-world experiments indicate a satisfactory performance, thereby demonstrating the feasibility of the proposed approach.

Robust guaranteed-cost path-following control for autonomous vehicles on unstructured roads

2017 ◽  
Vol 232 (7) ◽  
pp. 896-908 ◽  
Author(s):  
Jinghua Guo ◽  
Jin Wang ◽  
Ping Hu ◽  
Linhui Li
Keyword(s):  
Control System ◽  
Autonomous Vehicles ◽  
Path Following ◽  
Detection Algorithm ◽  
Parametric Uncertainties ◽  
Tracking Accuracy ◽  
Position Information ◽  
Path Following Control ◽  
Control Scheme ◽  
Guaranteed Cost

This paper deals with the problem of automatic path-following control for a class of autonomous vehicle systems with parametric uncertainties and external disturbances in cross-country conditions. In the unstructured environments, the unevenness, the discontinuity and the variability of the terrain greatly increase the parametric uncertainties and the external perturbations of autonomous vehicles. To overcome these difficulties, a novel automatic path-following control scheme of vision-based autonomous vehicles is presented by utilizing the guaranteed-cost control theory. First, a new road detection algorithm used for segmenting and extracting the traversable path in unstructured terrains is achieved by using a combination consisting of multiple sensors, and the local relative position information between the vehicles and the desired trajectories can be acquired by the proposed detected algorithm in real time. Then, an optimal guaranteed-cost path-following control system is proposed, which can deal with the parametric uncertainties of autonomous vehicles and ensure the stability of the closed-loop control system. Finally, both simulation tests and experimental results demonstrate that the proposed control scheme can guarantee high path-tracking accuracy irrespective of the parametric uncertainties.

Effects of Electrical Discharges in Low Pressure Gases on the Morphology of Polyethylene Crystals

1974 ◽  
Vol 32 ◽  
pp. 544-545
Author(s):  
L.H. Bolz ◽  
D.H. Reneker
Keyword(s):  
Power Distribution ◽  
Electrical Discharge ◽  
Dielectric Breakdown ◽  
Ionic Species ◽  
Low Pressure ◽  
Polymer Surfaces ◽  
Electrical Discharges ◽  
Adhesive Bonds ◽  
Power Distribution Lines ◽  
Modification Of The Surface

The attack, on the surface of a polymer, by the atomic, molecular and ionic species that are created in a low pressure electrical discharge in a gas is interesting because: 1) significant interior morphological features may be revealed, 2) dielectric breakdown of polymeric insulation on high voltage power distribution lines involves the attack on the polymer of such species created in a corona discharge, 3) adhesive bonds formed between polymer surfaces subjected to such SDecies are much stronger than bonds between untreated surfaces, 4) the chemical modification of the surface creates a reactive surface to which a thin layer of another polymer may be bonded by glow discharge polymerization.

Analysis of Lightning Overvoltages on Low Voltage Power Distribution Lines due to Direct Lightning Hits to Overhead Ground Wire

1993 ◽  
Vol 113 (8) ◽  
pp. 881-888 ◽  
Author(s):  
Yasutomo Imai ◽  
Nobuyuki Fujiwara ◽  
Hiroshi Yokoyama ◽  
Tetsuro Shimomura ◽  
Koichi Yamaoka ◽  
...  
Keyword(s):  
Power Distribution ◽  
Low Voltage ◽  
Distribution Lines ◽  
Power Distribution Lines

scholarly journals Time- and Resource-Efficient Time-to-Collision Forecasting for Indoor Pedestrian Obstacles Avoidance

2021 ◽  
Vol 7 (4) ◽  
pp. 61
Author(s):  
David Urban ◽  
Alice Caplier
Keyword(s):  
Neural Network ◽  
Autonomous Vehicles ◽  
Depth Estimation ◽  
Video Camera ◽  
Obstacle Detection ◽  
Navigation Systems ◽  
Time To Collision ◽  
Static Data ◽  
Monocular Depth ◽  
Fully Connected

As difficult vision-based tasks like object detection and monocular depth estimation are making their way in real-time applications and as more light weighted solutions for autonomous vehicles navigation systems are emerging, obstacle detection and collision prediction are two very challenging tasks for small embedded devices like drones. We propose a novel light weighted and time-efficient vision-based solution to predict Time-to-Collision from a monocular video camera embedded in a smartglasses device as a module of a navigation system for visually impaired pedestrians. It consists of two modules: a static data extractor made of a convolutional neural network to predict the obstacle position and distance and a dynamic data extractor that stacks the obstacle data from multiple frames and predicts the Time-to-Collision with a simple fully connected neural network. This paper focuses on the Time-to-Collision network’s ability to adapt to new sceneries with different types of obstacles with supervised learning.

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