Passive Air Leakage Detection Mechanism for a Vacuum Suction Actuator

2021 ◽  
Author(s):  
Seung Ho Lee ◽  
Dong Jun Oh ◽  
Ja Choon Koo
Keyword(s):  
Moving Objects ◽  
Brake System ◽  
Leakage Detection ◽  
Air Leakage ◽  
Multiple Objects ◽  
Detection Mechanism ◽  
Vacuum Suction ◽  
Passive Compliance ◽  
Spring Mechanism

Abstract Recently, research on vacuum actuators for holding and transporting objects has been actively conducted. In particular, many vacuum actuators are used to hold and transport several objects at once. However, there is a possibility that a problem of reducing vacuum efficiency may occur when several vacuum actuators are used simultaneously in the process of transporting multiple objects. The first factor is that, due to the diversity of the object’s shape, the vacuum pad of some actuators may not touch the object, so that gripping may not occur. Second, some actuators’ vacuum pad touches the object, but the pad is not completely blocked, resulting in air leakage. This paper used a spring mechanism to solve this problem and developed a vacuum gripping actuator that can block airflow into the actuator that is not used for vacuum efficiency when driving the system before the system is driven. Due to the spring inside the actuator that can play the role of passive compliance, the length can be adjusted, so even if the distance to the object is not constant, it can hold and transport several objects. Furthermore, the pretension of the spring makes it possible to block air inflow initially. We have also developed a brake system using pneumatic and tendon to hold the actuators to maintain each actuator’s length when holding and moving objects. We unified the driving method for operating both systems for simplicity by receiving pneumatic pressure from a pneumatic compressor.

scholarly journals Object detection and tracking in video sequences: formalization, metrics and results

Informatics ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 43-60
Author(s):  
R. P. Bohush ◽  
S. V. Ablameyko
Keyword(s):  
Moving Objects ◽  
Human Movement ◽  
Video Sequences ◽  
Multiple Objects ◽  
Movement Trajectories ◽  
Detection And Tracking ◽  
Form Features ◽  
One And Many ◽  
Tracking Objects

One of the promising areas of development and implementation of artificial intelligence is the automatic detection and tracking of moving objects in video sequence. The paper presents a formalization of the detection and tracking of one and many objects in video. The following metrics are considered: the quality of detection of tracked objects, the accuracy of determining the location of the object in a frame, the trajectory of movement, the accuracy of tracking multiple objects. Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. Neural network features are included in a composite descriptor that also contains geometric and color features to describe each detected person in the frame. The results of experiments based on the considered criteria are presented, and it is experimentally confirmed that the improvement of the detector operation makes it possible to increase the accuracy of tracking objects. Examples of frames of processed video sequences with visualization of human movement trajectories are presented.

scholarly journals What is in a Viral Stock: Perspectives and Current Limitations of Flow Virometry

2020 ◽  
Author(s):  
Timothy K. Soh ◽  
Jens B. Bosse
Keyword(s):  
Flow Cytometry ◽  
Full Potential ◽  
Multiple Objects ◽  
Virus Particles ◽  
Viral Particles ◽  
Viral Stock ◽  
Infected Cells ◽  
A Minor ◽  
Unique Capability

Herpesviruses produce a plethora of pleomorphic and heterogeneous particle populations. The composition and biological role of these is not understood. Detailed analysis has been challenging due to the lack of multidimensional identification and purification methodologies. Fluorescence-activated cell sorting (FACS), originally developed to sort objects with at least ten thousand-fold larger volumes, has recently been applied to cellular exosomes as well as viral particles and has been dubbed nanoscale flow cytometry or “flow virometry”. In comparison to other nanoparticles, herpesvirus concentrations can be measured with high precision using simple culturing methods. Here, we used this unique capability to evaluate a standard FACS sorter. We demonstrate that detection and separation capabilities were insufficient to distinguish infectious fluorescent viral populations from populations lacking fluorescence and infectivity. Moreover, fluorescent populations did not contain single virus particles but mostly aggregates. On top, analysis of viral samples by flow cytometry was confounded by swarm detection, as multiple objects are measured simultaneously and interpreted as a single object. Despite these technical difficulties, comparison of crude supernatant to gradient purified HCMV revealed that infectious virus is a minor proportion of the particles released from infected cells. Our data stress the need for a set of standardized controls and protocols when applying FACS to biological nanoparticles and highlights technical challenges that need to be solved before flow virometry can achieve its full potential.

scholarly journals Game Control Methods Comparison when Avoiding Collisions with Multiple Objects Using Radar Remote Sensing

2020 ◽  
Vol 12 (10) ◽  
pp. 1573
Author(s):  
Józef Lisowski
Keyword(s):  
Remote Sensing ◽  
Differential Game ◽  
Moving Objects ◽  
Computer Control ◽  
Matrix Game ◽  
Multiple Objects ◽  
State Equations ◽  
Radar Remote Sensing ◽  
Control Programs ◽  
Game Environment

This article formulates the concept of games in the field of process control theory in marine sciences and reviews the literature on the possible applications of games. The possible types of game control processes for moving objects are presented. A computer-aided object safe control in the game environment, with an appropriate steering system, is described based on radar remote sensing in order to avoid collisions with many other objects that are encountered. First, the basic model of object movement in the game environment is presented as a differential game with many objects, described by appropriate game state equations, state and steering restrictions, and a quality control index in the form of an integral and final payment of the game. Next, the surrogate models of the differential game are described in detail for the development of practical computer control programs using positional and matrix game models. Particular attention, in each type of game, is paid to the aspect of cooperation or lack of cooperation between objects in making maneuvering decisions. A computer simulation illustrates these considerations with game control programs at a sea-crossing situation where multiple objects were encountered. Safe object trajectories are compared using two methods of game control using positional and matrix game models while also considering cases with cooperation or non-cooperation of objects.

Tracking Multiple Objects Is Limited Only by Object Spacing, Not by Speed, Time, or Capacity

2010 ◽  
Vol 21 (7) ◽  
pp. 920-925 ◽  
Author(s):  
S.L. Franconeri ◽  
S.V. Jonathan ◽  
J.M. Scimeca
Keyword(s):  
Object Tracking ◽  
Moving Objects ◽  
Multiple Object Tracking ◽  
Single Object ◽  
Multiple Objects ◽  
Performance Constraints ◽  
Root Cause ◽  
Multiple Object ◽  
Tracking Time ◽  
Environment Performance

In dealing with a dynamic world, people have the ability to maintain selective attention on a subset of moving objects in the environment. Performance in such multiple-object tracking is limited by three primary factors—the number of objects that one can track, the speed at which one can track them, and how close together they can be. We argue that this last limit, of object spacing, is the root cause of all performance constraints in multiple-object tracking. In two experiments, we found that as long as the distribution of object spacing is held constant, tracking performance is unaffected by large changes in object speed and tracking time. These results suggest that barring object-spacing constraints, people could reliably track an unlimited number of objects as fast as they could track a single object.

scholarly journals An Adaptive End-to-End Classification Approach for Mobile Laser Scanning Point Clouds Based on Knowledge in Urban Scenes

2019 ◽  
Vol 11 (2) ◽  
pp. 186 ◽  
Author(s):  
Mingxue Zheng ◽  
Huayi Wu ◽  
Yong Li
Keyword(s):  
Laser Scanning ◽  
Point Clouds ◽  
Basic Knowledge ◽  
Multiple Objects ◽  
Urban Scenes ◽  
Knowledge Based ◽  
Training Samples ◽  
End To End ◽  
Heavy Training

It is fundamental for 3D city maps to efficiently classify objects of point clouds in urban scenes. However, it is still a large challenge to obtain massive training samples for point clouds and to sustain the huge training burden. To overcome it, a knowledge-based approach is proposed. The knowledge-based approach can explore discriminating features of objects based on people’s understanding of the surrounding environment, which exactly replaces the role of training samples. To implement the approach, a two-step segmentation procedure is carried out in this paper. In particular, Fourier Fitting is applied for second adaptive segmentation to separate points of multiple objects lying within a single group of the first segmentation. Then height difference and three geometrical eigen-features are extracted. In comparison to common classification methods, which need massive training samples, only basic knowledge of objects in urban scenes is needed to build an end-to-end match between objects and extracted features in the proposed approach. In addition, the proposed approach has high computational efficiency because of no heavy training process. Qualitative and quantificational experimental results show the proposed approach has promising performance for object classification in various urban scenes.

The Localization of the Wind Turbine Passive Spindle Brake Based on Mechanical Mechanics

2014 ◽  
Vol 540 ◽  
pp. 96-105 ◽  
Author(s):  
Hong Mei Sun ◽  
Li Wei Hu ◽  
Jia Wen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Brake System ◽  
Harsh Environments ◽  
Test Results ◽  
Advantages And Disadvantages ◽  
System Composition ◽  
Analytical Test ◽  
Doubly Fed

Wind turbines typically run in harsh environments region, but the general requirements in the case of work unattended. Therefore, the brake system is a key component to protect the safe operation of wind turbines. When the wind turbine over speed occurs, overload or other abnormal conditions, the brake system needs to start immediately, so that the whole unit into the shutdown state to ensure crew safety. This article describes the role of wind turbine brake system, composition, operation principle, comparing the advantages and disadvantages of the most commonly used active and passive spindle brake doubly-fed wind turbine. Completion of a wind turbine import passive brake design, manufacturing localization, combined with wind turbine machine operating parameters, developed analytical test program brakes and the test results, and for the test questions are designed to improve.

Multiple Objects Tracking Based on Mixture Features

2014 ◽  
Vol 945-949 ◽  
pp. 1869-1874
Author(s):  
Dong Mei Li ◽  
Tao Li
Keyword(s):  
Target Tracking ◽  
Moving Objects ◽  
Coincidence Degree ◽  
Multiple Target Tracking ◽  
Multiple Target ◽  
Multiple Objects ◽  
Current Frame ◽  
Complex Scenes ◽  
Objects Tracking ◽  
Tracking Object

For multiple objects tracking in complex scenes, this paper proposes a new tracking algorithm for multiple moving objects. The algorithm makes likelihood calculation by using new DG_CENTRIST feature and color feature, and then calculates the overlapping ratio of the tracking object and the object in the current frame using coincidence degree to measure the occlusion. The algorithm has good robustness and stability, and the experiment results show that this method can effectively improve the accuracy of the multiple target tracking.

Revisiting the Role of the Fusiform Face Area in Expertise

2016 ◽  
Vol 28 (9) ◽  
pp. 1345-1357 ◽  
Author(s):  
Merim Bilalić
Keyword(s):  
Pattern Analysis ◽  
Spatial Relations ◽  
Fusiform Face Area ◽  
Multivariate Pattern Analysis ◽  
Multiple Objects ◽  
Activation Patterns ◽  
Face Area ◽  
Single Category ◽  
Multivariate Pattern

The fusiform face area (FFA) is considered to be a highly specialized brain module because of its central importance for face perception. However, many researchers claim that the FFA is a general visual expertise module that distinguishes between individual examples within a single category. Here, I circumvent the shortcomings of some previous studies on the FFA controversy by using chess stimuli, which do not visually resemble faces, together with more sensitive methods of analysis such as multivariate pattern analysis. I also extend the previous research by presenting chess positions, complex scenes with multiple objects, and their interrelations to chess experts and novices as well as isolated chess objects. The first experiment demonstrates that chess expertise modulated the FFA activation when chess positions were presented. In contrast, single chess objects did not produce different activation patterns among experts and novices even when the multivariate pattern analysis was used. The second experiment focused on the single chess objects and featured an explicit task of identifying the chess objects but failed to demonstrate expertise effects in the FFA. The experiments provide support for the general expertise view of the FFA function but also extend the scope of our understanding about the function of the FFA. The FFA does not merely distinguish between different exemplars within the same category of stimuli. More likely, it parses complex multiobject stimuli that contain numerous functional and spatial relations.

scholarly journals The Application of Image Processing to Solve Occlusion Issue in Object Tracking

2018 ◽  
Vol 152 ◽  
pp. 03001
Author(s):  
Yun Zhe Cheong ◽  
Wei Jen Chew
Keyword(s):  
Object Tracking ◽  
Moving Objects ◽  
Object Segmentation ◽  
Target Object ◽  
Occlusion Handling ◽  
Multiple Objects ◽  
The Road ◽  
Occluded Objects ◽  
On The Road ◽  
Tracking Object

Object tracking is a computer vision field that involves identifying and tracking either a single or multiple objects in an environment. This is extremely useful to help observe the movements of the target object like people in the street or cars on the road. However, a common issue with tracking an object in an environment with many moving objects is occlusion. Occlusion can cause the system to lose track of the object being tracked or after overlapping, the wrong object will be tracked instead. In this paper, a system that is able to correctly track occluded objects is proposed. This system includes algorithms such as foreground object segmentation, colour tracking, object specification and occlusion handling. An input video is input to the system and every single frame of the video is analysed. The foreground objects are segmented with object segmentation algorithm and tracked with the colour tracking algorithm. An ID is assigned to each tracked object. Results obtained shows that the proposed system is able to continuously track an object and maintain the correct identity even after is has been occluded by another object.

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