Computer control of an autonomous road vehicle by computer vision

2002 ◽  
Author(s):  
J. Manigel ◽  
W. Leonhard
Keyword(s):  
Computer Vision ◽  
Computer Control ◽  
Road Vehicle

Computer Control with Hand Gestures Using Computer Vision

2020 ◽  
Author(s):  
Nirmala J S ◽  
Ajeet Kumar ◽  
Adith Jose E A ◽  
Kapil Kumar ◽  
Abhishek R Malvadkar
Keyword(s):  
Computer Vision ◽  
Computer Control ◽  
Hand Gestures

Developing Algorithms for a Berry Recognition System Used in Robotized Harvesting of Garden Strawberry

2020 ◽  
Vol 67 (1) ◽  
pp. 133-141
Author(s):  
Dmitriy O. Khort ◽  
Aleksei I. Kutyrev ◽  
Igor G. Smirnov ◽  
Rostislav A. Filippov ◽  
Roman V. Vershinin
Keyword(s):  
Computer Vision ◽  
Technological Process ◽  
Degrees Of Freedom ◽  
Computer Control ◽  
Recognition System ◽  
Raspberry Pi ◽  
Laser Sensors ◽  
Lighting Conditions ◽  
Systems Research ◽  
Degree Of Maturity

Technological capabilities of agricultural units cannot be optimally used without extensive automation of production processes and the use of advanced computer control systems. (Research purpose) To develop an algorithm for recognizing the coordinates of the location and ripeness of garden strawberries in different lighting conditions and describe the technological process of its harvesting in field conditions using a robotic actuator mounted on a self-propelled platform. (Materials and methods) The authors have developed a self-propelled platform with an automatic actuator for harvesting garden strawberry, which includes an actuator with six degrees of freedom, a co-axial gripper, mg966r servos, a PCA9685 controller, a Logitech HD C270 computer vision camera, a single-board Raspberry Pi 3 Model B+ computer, VL53L0X laser sensors, a SZBK07 300W voltage regulator, a Hubsan X4 Pro H109S Li-polymer battery. (Results and discussion) Using the Python programming language 3.7.2, the authors have developed a control algorithm for the automatic actuator, including operations to determine the X and Y coordinates of berries, their degree of maturity, as well as to calculate the distance to berries. It has been found that the effectiveness of detecting berries, their area and boundaries with a camera and the OpenCV library at the illumination of 300 Lux reaches 94.6 percent’s. With an increase in the robotic platform speed to 1.5 kilometre per hour and at the illumination of 300 Lux, the average area of the recognized berries decreased by 9 percent’s to 95.1 square centimeter, at the illumination of 200 Lux, the area of recognized berries decreased by 17.8 percent’s to 88 square centimeter, and at the illumination of 100 Lux, the area of recognized berries decreased by 36.4 percent’s to 76 square centimeter as compared to the real area of berries. (Conclusions) The authors have provided rationale for the technological process and developed an algorithm for harvesting garden strawberry using a robotic actuator mounted on a self-propelled platform. It has been proved that lighting conditions have a significant impact on the determination of the area, boundaries and ripeness of berries using a computer vision camera.

Development of a Human Factors Research Laboratory for Off-Road Vehicle Operator Workstation Design

1982 ◽  
Vol 26 (10) ◽  
pp. 896-900 ◽  
Author(s):  
J. R. Duncan ◽  
E. L. Wegscheid
Keyword(s):  
Human Factors ◽  
Research Laboratory ◽  
Degrees Of Freedom ◽  
Human Performance ◽  
Computer Control ◽  
Road Vehicle ◽  
Motion Simulator ◽  
Vehicle Motion ◽  
Simulator Motion ◽  
Human Factors Research

A new human factors research laboratory has been developed to provide reliable human-performance data for the design of improved off-road vehicle operator workstations. The principal research tool within this laboratory is a vehicle operations simulator. The simulator consists of a hydraulically driven platform upon which a vehicle operator's enclosure or workstation can be mounted. Under computer control, the simulator is capable of motion with six degrees-of-freedom. With this capability, the simulator's motion can be programmed to reproduce operator workstation vibration experienced in operational field environments. Both field recorded data and mathematical simulations of existing and proposed vehicles can be used to command the simulator motion. In addition to simulating vehicle motion, the simulator is capable of producing realistic control and monitoring tasks for the operator, as well as operator enclosure environmental conditions. This paper describes the research objectives for which the simulator was built, the specifications used in the design of the vehicle motion simulator system, the hardware selected in implementing that design, and the computer control used to simulate both field and artificial “ride” histories.

scholarly journals Road Vehicle Monitoring System Based on Intelligent Visual Internet of Things

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Qingwu Li ◽  
Haisu Cheng ◽  
Yan Zhou ◽  
Guanying Huo
Keyword(s):  
Computer Vision ◽  
Internet Of Things ◽  
Monitoring System ◽  
Rapid Development ◽  
Weather Condition ◽  
License Plate ◽  
Surveillance Systems ◽  
Road Vehicle ◽  
Intelligent Surveillance ◽  
Vehicle Monitoring

In recent years, with the rapid development of video surveillance infrastructure, more and more intelligent surveillance systems have employed computer vision and pattern recognition techniques. In this paper, we present a novel intelligent surveillance system used for the management of road vehicles based on Intelligent Visual Internet of Things (IVIoT). The system has the ability to extract the vehicle visual tags on the urban roads; in other words, it can label any vehicle by means of computer vision and therefore can easily recognize vehicles with visual tags. The nodes designed in the system can be installed not only on the urban roads for providing basic information but also on the mobile sensing vehicles for providing mobility support and improving sensing coverage. Visual tags mentioned in this paper consist of license plate number, vehicle color, and vehicle type and have several additional properties, such as passing spot and passing moment. Moreover, we present a fast and efficient image haze removal method to deal with haze weather condition. The experiment results show that the designed road vehicle monitoring system achieves an average real-time tracking accuracy of 85.80% under different conditions.

Microdensitometer—computer correlation analysis of ultrastructural periodicity

1978 ◽  
Vol 36 (2) ◽  
pp. 32-33
Author(s):  
D.R. Ensor ◽  
C.G. Jensen ◽  
J.A. Fillery ◽  
R.J.K. Baker
Keyword(s):  
Correlation Analysis ◽  
Background Noise ◽  
Computer Control ◽  
Optical Diffraction ◽  
Screw Thread ◽  
Straight Line ◽  
Computer Storage ◽  
Correlation Process ◽  
Electron Microscope Image ◽  
Fixed Beam

Because periodicity is a major indicator of structural organisation numerous methods have been devised to demonstrate periodicity masked by background “noise” in the electron microscope image (e.g. photographic image reinforcement, Markham et al, 1964; optical diffraction techniques, Horne, 1977; McIntosh,1974). Computer correlation analysis of a densitometer tracing provides another means of minimising "noise". The correlation process uncovers periodic information by cancelling random elements. The technique is easily executed, the results are readily interpreted and the computer removes tedium, lends accuracy and assists in impartiality.A scanning densitometer was adapted to allow computer control of the scan and to give direct computer storage of the data. A photographic transparency of the image to be scanned is mounted on a stage coupled directly to an accurate screw thread driven by a stepping motor. The stage is moved so that the fixed beam of the densitometer (which is directed normal to the transparency) traces a straight line along the structure of interest in the image.

Defocus ramp correction in spot-scan imaging

1992 ◽  
Vol 50 (1) ◽  
pp. 130-131
Author(s):  
Kenneth H. Downing
Keyword(s):  
Computer Control ◽  
Three Dimensional ◽  
Sufficient Accuracy ◽  
Objective Lens ◽  
Electron Crystallography ◽  
Contrast Transfer Function ◽  
Tilt Axis ◽  
Specimen Height ◽  
The Difference ◽  
Envelope Functions

Three-dimensional structures of a number of samples have been determined by electron crystallography. The procedures used in this work include recording images of fairly large areas of a specimen at high tilt angles. There is then a large defocus ramp across the image, and parts of the image are far out of focus. In the regions where the defocus is large, the contrast transfer function (CTF) varies rapidly across the image, especially at high resolution. Not only is the CTF then difficult to determine with sufficient accuracy to correct properly, but the image contrast is reduced by envelope functions which tend toward a low value at high defocus.We have combined computer control of the electron microscope with spot-scan imaging in order to eliminate most of the defocus ramp and its effects in the images of tilted specimens. In recording the spot-scan image, the beam is scanned along rows that are parallel to the tilt axis, so that along each row of spots the focus is constant. Between scan rows, the objective lens current is changed to correct for the difference in specimen height from one scan to the next.

Applications of CCEM to Environmental Health Problems

1985 ◽  
Vol 43 ◽  
pp. 102-103
Author(s):  
R. J. Lee ◽  
J. S. Walker
Keyword(s):  
Electron Microscopy ◽  
Image Analysis ◽  
Environmental Health ◽  
Computer Control ◽  
External Agent ◽  
External Agents ◽  
Computer Controlled ◽  
Primitive State ◽  
Textural Changes ◽  
General Aspects

Electron microscopy (EM), with the advent of computer control and image analysis techniques, is rapidly evolving from an interpretative science into a quantitative technique. Electron microscopy is potentially of value in two general aspects of environmental health: exposure and diagnosis.In diagnosis, electron microscopy is essentially an extension of optical microscopy. The goal is to characterize cellular changes induced by external agents. The external agent could be any foreign material, chemicals, or even stress. The use of electron microscopy as a diagnostic tool is well- developed, but computer-controlled electron microscopy (CCEM) has had only limited impact, mainly because it is fairly new and many institutions lack the resources to acquire the capability. In addition, major contributions to diagnosis will come from CCEM only when image analysis (IA) and processing algorithms are developed which allow the morphological and textural changes recognized by experienced medical practioners to be quantified. The application of IA techniques to compare cellular structure is still in a primitive state.

The Instructional SEM Laboratory at Iowa State University

1996 ◽  
Vol 54 ◽  
pp. 396-397
Author(s):  
L. S. Chumbley ◽  
M. Meyer ◽  
K. Fredrickson ◽  
F.C. Laabs
Keyword(s):  
Materials Science ◽  
Computer Network ◽  
Energy Dispersive Spectrometer ◽  
Computer Control ◽  
State University ◽  
Iowa State University ◽  
Internet Server ◽  
Schematic Layout ◽  
Hands On ◽  
Improve Instruction

The Materials Science Department at Iowa State University has developed a laboratory designed to improve instruction in the use of the scanning electron microscope (SEM). The laboratory makes use of a computer network and a series of remote workstations in a classroom setting to provide students with increased hands-on access to the SEM. The laboratory has also been equipped such that distance learning via the internet can be achieved.A view of the laboratory is shown in Figure 1. The laboratory consists of a JEOL 6100 SEM, a Macintosh Quadra computer that acts as a server for the network and controls the energy dispersive spectrometer (EDS), four Macintosh computers that act as remote workstations, and a fifth Macintosh that acts as an internet server. A schematic layout of the classroom is shown in Figure 2. The workstations are connected directly to the SEM to allow joystick and computer control of the microscope. An ethernet connection between the Quadra and the workstations allows students seated there to operate the EDS. Control of the microscope and joystick is passed between the workstations by a switch-box assembly that resides at the microscope console. When the switch-box assembly is activated a direct serial line is established between the specified workstation and the microscope via the SEM’s RS-232.

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