CMOS+FPGA vision system for visual feedback of mechanical systems

Shimizu, Kazuhiro; Hirai, Shinichi

doi:10.1109/robot.2006.1642008

Cited by 18 publications

(6 citation statements)

References 11 publications

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“…A vision system for visual feedback applied to control a mechanical system was proposed in [9]. In this approach a matched filter by correlation is used, which also determines the object's center of mass each 4,51 ms for small images (256 × 256 pixels).…”

Section: Related Workmentioning

confidence: 99%

An FPGA-Based Omnidirectional Vision Sensor for Motion Detection on Mobile Robots

Mori

Arias-García

Sánchez-Ferreira

et al. 2012

International Journal of Reconfigurable Computing

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This work presents the development of an integrated hardware/software sensor system for moving object detection and distance calculation, based on background subtraction algorithm. The sensor comprises a catadioptric system composed by a camera and a convex mirror that reflects the environment to the camera from all directions, obtaining a panoramic view. The sensor is used as an omnidirectional vision system, allowing for localization and navigation tasks of mobile robots. Several image processing operations such as filtering, segmentation and morphology have been included in the processing architecture. For achieving distance measurement, an algorithm to determine the center of mass of a detected object was implemented. The overall architecture has been mapped onto a commercial low-cost FPGA device, using a hardware/software co-design approach, which comprises a Nios II embedded microprocessor and specific image processing blocks, which have been implemented in hardware. The background subtraction algorithm was also used to calibrate the system, allowing for accurate results. Synthesis results show that the system can achieve a throughput of 26.6 processed frames per second and the performance analysis pointed out that the overall architecture achieves a speedup factor of 13.78 in comparison with a PC-based solution running on the real-time operating system xPC Target.

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Section: Related Workmentioning

confidence: 99%

An FPGA-Based Omnidirectional Vision Sensor for Motion Detection on Mobile Robots

Mori

Arias-García

Sánchez-Ferreira

et al. 2012

International Journal of Reconfigurable Computing

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“…Thereby, they can detect the positions of objects as rectangular image regions. When even higher throughput of hundreds or thousands of frames per second is required, systems with additional hardware support has been devised, in form of FPGAs [15,16,17] or specially designed chips [18]. Such systems can process all pixel in an image in parallel, allowing them to estimate local motion with very high speed.…”

Section: Related Workmentioning

confidence: 99%

Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components

Lampert

Peters

2010

J Real-Time Image Proc

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We describe RTblob, a high speed vision system that detects objects in cluttered scenes based on their color and shape at a speed of over 800 frames per second. Because the system is available as open-source software and relies only on off-the-shelf PC hardware components, it can provide the basis for multiple application scenarios. As an illustrative example, we show how RTblob can be used in a robotic table tennis scenario to estimate ball trajectories through 3D space simultaneously from four cameras images at a speed of 200 Hz.

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“…There have been some studies using real-time vision at high frame rates such as Column Parallel Vision (CPV) [4] and CMOS+FPGA vision [5] in manipulation tasks [6] and microscopic applications [7]. CPV has a general-purpose, massively parallel SIMD processor.…”

Section: High-speed Vision For Numerous-point Analysismentioning

confidence: 99%

955-fps Real-time Shape Measurement of a Moving/Deforming Object using High-speed Vision for Numerous-point Analysis

Watanabe

Komuro

Ishikawa

2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Abstract-This paper describes real-time shape measurement using a newly developed high-speed vision system. Our proposed measurement system can observe a moving/deforming object at high frame rate and can acquire data in real-time. This is realized by using two-dimensional pattern projection and a high-speed vision system with a massively parallel co-processor for numerous-point analysis. We detail our proposed shape measurement system and present some results of evaluation experiments. The experimental results show the advantages of our system compared with conventional approaches. I. INTRODUCTIONThere has been an increasing need for shape measurement techniques in a wide range of application fields. In particularly, approaches using vision are useful because of their contactless nature and flexibility. On the other hand, there are demands for improved performance such as accuracy, measurement range, time, cost and so on, and many kinds of systems have been developed to meet these demands [1].In this paper, we focus on the improvement of the measurement time and realize high-speed time-sequential shape measurement. This type of measurement will have a great impact on a wide variety of applications, such as control tasks for robotics; surgery support, for example, observation of a beating heart; rapid visual inspection of products; vehicle application, for example, checking road surfaces; and humanmachine interaction with high accuracy and flexibility.On the other hand, in such application fields, we need to observe a high-speed moving rigid-body and a deforming or vibrating non-rigid body. Conventional shape measurement, however, is mainly performed in situations where the relationships between the objects being measured and observation devices are completely known by ensuring stable or controllable conditions. Also, the performance of conventional systems in terms of throughput and latency is usually not good enough for real-time control applications; for example, throughput on the order of a thousand frames per second and latency on the order of milliseconds is generally required for robotic control.Based on these backgrounds, the feasible system is considered to have three requirements: (A) the ability to observe a moving object, (B) continuous observation at high frame rate, and (C) real-time acquisition of shape information. To realize these requirements, our proposed system employs an approach in which multiple spots in a single image of a shape are acquired using high-speed vision for numerouspoint analysis. As a result, the constructed system achieved 955-fps measurement of shape information with 4.5 ms

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CMOS+FPGA vision system for visual feedback of mechanical systems

Cited by 18 publications

References 11 publications

An FPGA-Based Omnidirectional Vision Sensor for Motion Detection on Mobile Robots

An FPGA-Based Omnidirectional Vision Sensor for Motion Detection on Mobile Robots

Real-time detection of colored objects in multiple camera streams with off-the-shelf hardware components

955-fps Real-time Shape Measurement of a Moving/Deforming Object using High-speed Vision for Numerous-point Analysis

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