Design, implementation, and verification of a low‐cost terminal guidance system for small fixed‐wing UAVs

2021 ◽  
Author(s):  
Yachao Yang ◽  
Chang Liu ◽  
Jie Li ◽  
Yu Yang ◽  
Juan Li ◽  
...  
Keyword(s):  
Low Cost ◽  
Guidance System ◽  
Terminal Guidance

Low cost audio based intelligent guidance system for visually impaired people

2020 ◽  
Vol 24 (03) ◽  
pp. 515-520
Author(s):  
Vattumilli Komal Venugopal ◽  
Alampally Naveen ◽  
Rajkumar R ◽  
Govinda K ◽  
Jolly Masih
Keyword(s):  
Visually Impaired ◽  
Low Cost ◽  
Guidance System ◽  
Visually Impaired People ◽  
Impaired People

scholarly journals A V-SLAM Guided and Portable System for Photogrammetric Applications

2021 ◽  
Vol 13 (12) ◽  
pp. 2351
Author(s):  
Alessandro Torresani ◽  
Fabio Menna ◽  
Roberto Battisti ◽  
Fabio Remondino
Keyword(s):  
Low Cost ◽  
Cost Effective ◽  
Motion Blur ◽  
Guidance System ◽  
Prototype System ◽  
Active Sensors ◽  
Localization And Mapping ◽  
Acquisition Speed ◽  
Mobile Mapping System ◽  
Slam Algorithm

Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System) also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.

Robust H∞ performance analysis framework for a missile terminal guidance system

2008 ◽  
Author(s):  
Ji Denggao ◽  
He Fenghua ◽  
Yao Yu ◽  
Liu Fuchun
Keyword(s):  
Performance Analysis ◽  
Guidance System ◽  
Analysis Framework ◽  
Terminal Guidance

scholarly journals Analysis of the Influence of Trace Point Step-Jump Behavior

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Yao Yang ◽  
Yang Xu ◽  
Pei Wang
Keyword(s):  
Recovery Time ◽  
Sliding Mode ◽  
Initial Step ◽  
Guidance System ◽  
Adjoint Model ◽  
Proportional Navigation ◽  
Guidance Law ◽  
Optimal Guidance ◽  
Fundamental Reason ◽  
Terminal Guidance

To explore the influence of the trace point step-jump behavior on a terminal guidance system, an analysis is performed from the line-of-sight rate (LOS rate) and guidance accuracy views for designing an anti-step-jump guidance law. First, the linear terminal guidance model under the trace point jump circumstance is constructed, and then the fundamental reason for the miss distance is investigated by deriving the upper bound of the LOS rate at the initial step-jump moment. Following this, the novel proposed analytical differential adjoint model is established with the adjoint method, and its validity is demonstrated comparing with the numeric derivative model. Based on the adjoint model, the effects of the ratio coefficient, the time constant, and the jump amplitude on the guidance accuracy are explored. Finally, a novel anti-step-jump guidance law is designed to shorten the recovery time of the overload. The simulations have shown that the faster recovery time and higher accuracy are achieved in comparison with the proportional navigation guidance, optimal guidance, and adaptive sliding mode guidance.

scholarly journals Intelligent Path Recognition against Image Noises for Vision Guidance of Automated Guided Vehicles in a Complex Workspace

2019 ◽  
Vol 9 (19) ◽  
pp. 4108 ◽  
Author(s):  
Wu ◽  
Sun ◽  
Zou ◽  
Xiao ◽  
Zhai
Keyword(s):  
Robot Navigation ◽  
Low Cost ◽  
Estimation Method ◽  
Automated Guided Vehicles ◽  
Guidance System ◽  
Mobile Robot Navigation ◽  
Model Parameters ◽  
Uniform Illumination ◽  
Vision Guidance ◽  
Open Question

Applying computer vision to mobile robot navigation has been studied more than twodecades. The most challenging problems for a vision-based AGV running in a complex workspaceinvolve the non-uniform illumination, sight-line occlusion or stripe damage, which inevitably resultin incomplete or deformed path images as well as many fake artifacts. Neither the fixed thresholdmethods nor the iterative optimal threshold methods can obtain a suitable threshold for the pathimages acquired on all conditions. It is still an open question to estimate the model parameters ofguide paths accurately by distinguishing the actual path pixels from the under- or oversegmentationerror points. Hence, an intelligent path recognition approach based on KPCA–BPNNand IPSO–BTGWP is proposed here, in order to resist the interferences from the complexworkspace. Firstly, curvilinear paths were recognized from their straight counterparts by means of apath classifier based on KPCA–BPNN. Secondly, an approximation method based on BTGWP wasdeveloped for replacing the curve with a series of piecewise lines (a polyline path). Thirdly, a robustpath estimation method based on IPSO was proposed to figure out the path parameters from a set ofpath pixels surrounded by noise points. Experimental results showed that our approach caneffectively improve the accuracy and reliability of a low-cost vision-guidance system for AGVs in acomplex workspace.

scholarly journals A Low-Cost Electromagnetic Docking Guidance System for Micro Autonomous Underwater Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 682 ◽  
Author(s):  
Shilin Peng ◽  
Jingbiao Liu ◽  
Junhao Wu ◽  
Chong Li ◽  
Benkun Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Guidance System ◽  
Electromagnetic Signal ◽  
Spatiotemporal Resolution ◽  
Search Coil ◽  
Wide Range ◽  
Processing Subsystem

As important observational platforms for the Smart Ocean concept, autonomous underwater vehicles (AUVs) that perform long-term observation in fleets are beneficial because they provide large-scale sampling data with a sufficient spatiotemporal resolution. Therefore, a large number of low-cost micro AUVs with docking capability for power recharge and data transmission are essential. This study designed a low-cost electromagnetic docking guidance (EMDG) system for micro AUVs. The EMDG system is composed of a transmitter coil located on the dock and a three-axial search coil magnetometer acting as a receiver. The search coil magnetometer was optimized for small sizes while maintaining sufficient sensitivity. The signal conditioning and processing subsystem was designed to calculate the deflection angle (β) for docking guidance. Underwater docking tests showed that the system can detect the electromagnetic signal and successfully guide AUV docking. The AUV can still perform docking in extreme positions, which cannot be realized through normal optical or acoustic guidance. This study is the first to focus on the EM guidance system for low-cost micro AUVs. The search coil sensor in the AUV is inexpensive and compact so that the system can be equipped on a wide range of AUVs.

scholarly journals Assistive guidance system for the visually impaired

2017 ◽  
Author(s):  
Rohit Takhar ◽  
Tushar Sharma ◽  
Udit Arora ◽  
Sohit Verma
Keyword(s):  
Credit Card ◽  
Visually Impaired ◽  
Low Cost ◽  
Histogram Equalization ◽  
Detection Algorithm ◽  
Contour Detection ◽  
Guidance System ◽  
Raspberry Pi ◽  
Pixel Intensity ◽  
Detection And Recognition

In recent years, with the improvement in imaging technology, the quality of small cameras have significantly improved. Coupled with the introduction of credit-card sized single-board computers such as Raspberry Pi, it is now possible to integrate a small camera with a wearable computer. This paper aims to develop a low cost product, using a webcam and Raspberry Pi, for visually-impaired people, which can assist them in detecting and recognising pedestrian crosswalks and staircases. There are two steps involved in detection and recognition of the obstacles i.e pedestrian crosswalks and staircases. In detection algorithm, we extract Haar features from the video frames and push these features to our Haar classifier. In recognition algorithm, we first convert the RGB image to HSV and apply histogram equalization to make the pixel intensity uniform. This is followed by image segmentation and contour detection. These detected contours are passed through a pre-processor which extracts the region of interests (ROI). We applied different statistical methods on these ROI to differentiate between staircases and pedestrian crosswalks. The detection and recognition results on our datasets demonstrate the effectiveness of our system.

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