Machine Vision System to Induct Binocular Wide-Angle Foveated Information into Both the Human and Computers - Feature Generation Algorithm based on DFT for Binocular Fixation

This paper introduces a machine vision system, which is suitable for cooperative works between the human and computer. This system provides images inputted from a stereo camera head not only to the processor but also to the user’s sight as binocular wide-angle foveated (WAF) information, thus it is applicable for Virtual Reality (VR) systems such as tele-existence or training experts. The stereo camera head plays a role to get required input images foveated by special wide-angle optics under camera view direction control and 3D head mount display (HMD) displays fused 3D images to the user. Moreover, an analog video signal processing device much inspired from a structure of the human visual system realizes a unique way to provide WAF information to plural processors and the user. Therefore, this developed vision system is also much expected to be applicable for the human brain and vision research, because the design concept is to mimic the human visual system. Further, an algorithm to generate features using Discrete Fourier Transform (DFT) for binocular fixation in order to provide well-fused 3D images to 3D HMD is proposed. This paper examines influences of applying this algorithm to space variant images such as WAF images, based on experimental results

Robot guidance using machine vision techniques in industrial environments: A comparative review

In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works

Improved Visible Light Communication Receiver Performance by Leveraging the Spatial Dimension

In wireless communications systems, signals can be transmitted as time (temporal) or spatial variants across 3D space, and in both ways. However, using temporal variant communication channels in high-speed data transmission introduces inter-symbol interference (ISI) which makes the systems unreliable. On the other hand, spatial diversity in signal processing reduces the ISI and improves the system throughput or performance by allowing more signals from different spatial locations at the same time. Therefore, the spatial features or properties of visible light signals can be very useful in designing a reliable visible light communication (VLC) system with higher system throughput and making it more robust against ambient noise and interference. By allowing only the signals of interest, spatial separability in VLC can minimize the noise to a greater extent to improve signal-to-noise ratio (SNR) which can ensure higher data rates (in the order of Gbps-Tbps) in VLC. So, designing a VLC system with spatial diversity is an exciting area to explore and might set the foundation for future VLC system architectures and enable different VLC based applications such as vehicular VLC, multi-VLC, localization, and detection using VLC, etc. This thesis work is motivated by the fundamental challenges in reusing spatial information in VLC systems to increase the system throughput or gain through novel system designing and their prototype implementations

Computer hardware and software for robotic control

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems

Design and implementation of robot skill programming and control

Abstract. Skill-based approach has been represented as a solution to the raising complicity of robot programming and control. The skills rely heavily on the use of sensors integrating sensor perceptions and robot actions, which enable the robot to adapt to changes and uncertainties in the real world and operate autonomously. The aim of this thesis was to design and implement a programming concept for skill-based control of industrial robots. At the theoretical part of this thesis, the industrial robot system is introduced as well as some basic concepts of robotics. This is followed by the introduction of different robot programming and 3D machine vision methods. At the last section of the theoretical part, the structure of skill-based programs is presented. In the experimental part, structure of the skills required for the “grinding with localization” -task are presented. The task includes skills such as global localization with 3D-depth sensor, scanning the object with 2D-profile scanner, precise localization of the object as well as two grinding skills: level surface grinding and straight seam grinding. Skills are programmed with an off-line programming tool and implemented in a robot cell, composed of a standard industrial robot with grinding tools, 3D-depth sensors and 2D-profile scanners. The results show that global localization can be carried out with consumer class 3D-depth sensors and more accurate local localization with an industrial high-accuracy 2D-profile scanner attached to the robot’s flange. The grinding experiments and tests were focused on finding suitable structures of the skill programs as well as to understand how the different parameters influence on the quality of the grinding.Robotin taitopohjaisten ohjelmien ohjelmointi ja testaus. Tiivistelmä. Robotin taitopohjaisia ohjelmia on esitetty ratkaisuksi robottien jatkuvasti monimutkaistuvaan ohjelmointiin. Taidot pohjautuvat erilaisten antureiden ja robotin toimintojen integroimiseen, joiden avulla robotti pystyy havainnoimaan muutokset reaalimaailmassa ja toimimaan autonomisesti. Tämän työn tavoitteena oli suunnitella ja toteuttaa taitopohjaisia ohjelmia teollisuusrobotille. Aluksi työn teoriaosuudessa esitellään teollisuusrobottijärjestelmään kuuluvia osia ja muutamia robotiikan olennaisimpia käsitteitä. Sen jälkeen käydään läpi eri robotin ohjelmointitapoja ja eri 3D-konenäön toimintaperiaatteita. Teoriaosuuden lopussa esitellään taitopohjaisten ohjelmien rakennetta. Käytännön osuudessa esitellään ”hionta paikoituksella” -tehtävän suoritukseen tarvittavien taitojen rakenne. Tehtävän vaatimia taitoja ovat muun muassa kappaleen globaalipaikoitus 3D-syvyyskameralla, kappaleen skannaus 2D-profiiliskannerilla, kappaleen tarkkapaikoitus ja kaksi eri hiontataitoa: tasomaisen pinnan ja suoran sauman hionta. Taidot ohjelmoidaan off-line ohjelmointityökalulla ja implementoidaan robottisoluun, joka muodostuu hiontatyökaluilla varustetusta teollisuusrobotista, 3D-kameroista ja 2D-profiiliskannereista. Työn tuloksista selviää, että kappaleen globaalipaikoitus voidaan suorittaa kuluttajille suunnatuilla 3D-syvyyskameroilla ja kappaleen tarkempi lokaalipaikoitus robotin ranteeseen kiinnitetyllä teollisuuden käyttämillä 2D-profiiliskannereilla. Hiontojen kokeellisessa osuudessa etsitään ohjelmien oikeanlaista rakennetta sekä muodostetaan käsitys eri parametrien vaikutuksesta hionnan laatuun

ENHANCEMENTS TO THE MODIFIED COMPOSITE PATTERN METHOD OF STRUCTURED LIGHT 3D CAPTURE

The use of structured light illumination techniques for three-dimensional data acquisition is, in many cases, limited to stationary subjects due to the multiple pattern projections needed for depth analysis. Traditional Composite Pattern (CP) multiplexing utilizes sinusoidal modulation of individual projection patterns to allow numerous patterns to be combined into a single image. However, due to demodulation artifacts, it is often difficult to accurately recover the subject surface contour information. On the other hand, if one were to project an image consisting of many thin, identical stripes onto the surface, one could, by isolating each stripe center, recreate a very accurate representation of surface contour. But in this case, recovery of depth information via triangulation would be quite difficult. The method described herein, Modified Composite Pattern (MCP), is a conjunction of these two concepts. Combining a traditional Composite Pattern multiplexed projection image with a pattern of thin stripes allows for accurate surface representation combined with non-ambiguous identification of projection pattern elements. In this way, it is possible to recover surface depth characteristics using only a single structured light projection. The technique described utilizes a binary structured light projection sequence (consisting of four unique images) modulated according to Composite Pattern methodology. A stripe pattern overlay is then applied to the pattern. Upon projection and imaging of the subject surface, the stripe pattern is isolated, and the composite pattern information demodulated and recovered, allowing for 3D surface representation. In this research, the MCP technique is considered specifically in the context of a Hidden Markov Process Model. Updated processing methodologies explained herein make use of the Viterbi algorithm for the purpose of optimal analysis of MCP encoded images. Additionally, we techniques are introduced which, when implemented, allow fully automated processing of the Modified Composite Pattern image