scholarly journals Human–Robot–Environment Interaction Interface for Smart Walker Assisted Gait: AGoRA Walker

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2897 ◽  
Author(s):  
Sergio D. Sierra Sierra M. ◽  
Mario Garzón ◽  
Marcela Múnera ◽  
Carlos A. Cifuentes
Keyword(s):  
Detection System ◽  
Control Strategies ◽  
User Interaction ◽  
Human Detection ◽  
Environment Interaction ◽  
Mobility Impairments ◽  
System A ◽  
Interaction System ◽  
Interaction Interface ◽  
Smart Walker

The constant growth of the population with mobility impairments has led to the development of several gait assistance devices. Among these, smart walkers have emerged to provide physical and cognitive interactions during rehabilitation and assistance therapies, by means of robotic and electronic technologies. In this sense, this paper presents the development and implementation of a human–robot–environment interface on a robotic platform that emulates a smart walker, the AGoRA Walker. The interface includes modules such as a navigation system, a human detection system, a safety rules system, a user interaction system, a social interaction system and a set of autonomous and shared control strategies. The interface was validated through several tests on healthy volunteers with no gait impairments. The platform performance and usability was assessed, finding natural and intuitive interaction over the implemented control strategies.

scholarly journals First Successful Rescue of a Lost Person Using the Human Detection System: A Case Study from Beskid Niski (SE Poland)

2021 ◽  
Vol 13 (23) ◽  
pp. 4903
Author(s):  
Tomasz Niedzielski ◽  
Mirosława Jurecka ◽  
Bartłomiej Miziński ◽  
Wojciech Pawul ◽  
Tomasz Motyl
Keyword(s):  
Detection System ◽  
Search And Rescue ◽  
Human Detection ◽  
Aerial Images ◽  
Rescue Service ◽  
Se Poland ◽  
System A ◽  
Close Range ◽  
Automated Algorithms

Recent advances in search and rescue methods include the use of unmanned aerial vehicles (UAVs), to carry out aerial monitoring of terrains to spot lost individuals. To date, such searches have been conducted by human observers who view UAV-acquired videos or images. Alternatively, lost persons may be detected by automated algorithms. Although some algorithms are implemented in software to support search and rescue activities, no successful rescue case using automated human detectors has been reported on thus far in the scientific literature. This paper presents a report from a search and rescue mission carried out by Bieszczady Mountain Rescue Service near the village of Cergowa in SE Poland, where a 65-year-old man was rescued after being detected via use of SARUAV software. This software uses convolutional neural networks to automatically locate people in close-range nadir aerial images. The missing man, who suffered from Alzheimer’s disease (as well as a stroke the previous day) spent more than 24 h in open terrain. SARUAV software was allocated to support the search, and its task was to process 782 nadir and near-nadir JPG images collected during four photogrammetric flights. After 4 h 31 min of the analysis, the system successfully detected the missing person and provided his coordinates (uploading 121 photos from a flight over a lost person; image processing and verification of hits lasted 5 min 48 s). The presented case study proves that the use of an UAV assisted by SARUAV software may quicken the search mission.

Design of Surface Contour Detection System Based on SCM

2014 ◽  
Vol 945-949 ◽  
pp. 2137-2140
Author(s):  
Miao Miao Tan ◽  
Zi Yi Zhang
Keyword(s):  
Real Time ◽  
Detection System ◽  
Contour Detection ◽  
Displacement Sensor ◽  
Laser Displacement Sensor ◽  
System A ◽  
Factors Influencing ◽  
Surface Contour ◽  
Interaction Interface ◽  
Close Range

An automatic surface contour detection system was designed. The detection precision of two sensors and the transmission accuracy of screw were important factors influencing the characteristics of the detection system. A laser displacement sensor and cable-displacement sensor were chosen in this system, which both have high precision and easy work principles. Bluetooth module could realize interaction between SCM and PC reliably and quickly in close range. After programming interaction interface using LabView, the surface contour of measured part could be acquired in real-time.

Deep convolutional neural networks for human movement detection using wireless signals

2021 ◽  
pp. 1-10
Author(s):  
Chien-Cheng Leea ◽  
Zhongjian Gao ◽  
Xiu-Chi Huanga
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Convolutional Neural Network ◽  
Detection System ◽  
Deep Convolutional Neural Network ◽  
Human Detection ◽  
Two Dimensional ◽  
Dimensional Matrix ◽  
State Classification ◽  
Propagation Paths

This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet’s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective.

Fabrication of Three-Dimensional Micro-Structures with Two-Photon Absorption by Femtosecond Laser

2006 ◽  
Vol 532-533 ◽  
pp. 568-571
Author(s):  
Ming Zhou ◽  
Hai Feng Yang ◽  
Li Peng Liu ◽  
Lan Cai
Keyword(s):  
Photonic Crystal ◽  
Femtosecond Laser ◽  
Detection System ◽  
Three Dimensional ◽  
Photon Absorption ◽  
Micro Fabrication ◽  
Two Photon Absorption ◽  
Two Photon ◽  
Photo Polymerization ◽  
System A

The photo-polymerization induced by Two-Photon Absorption (TPA) is tightly confined in the focus because the efficiency of TPA is proportional to the square of intensity. Three-dimensional (3D) micro-fabrication can be achieved by controlling the movement of the focus. Based on this theory, a system for 3D-micro-fabrication with femtosecond laser is proposed. The system consists of a laser system, a microscope system, a real-time detection system and a 3D-movement system, etc. The precision of micro-machining reaches a level down to 700nm linewidth. The line width was inversely proportional to the fabrication speed, but proportional to laser power and NA. The experiment results were simulated, beam waist of 0.413μm and TPA cross section of 2×10-54cm4s was obtained. While we tried to optimize parameters, we also did some research about its applications. With TPA photo-polymerization by means of our experimental system, 3D photonic crystal of wood-pile structure twelve layers and photonic crystal fiber are manufactured. These results proved that the micro-fabrication system of TPA can not only obtain the resolution down to sub-micron level, but also realize real 3D micro-fabrication.

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