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.

/pdf/an-fpga-based-omnidirectional-vision-sensor-for-motion-29kbfjdzcs.pdf

An FPGA-based omnidirectional vision sensor for motion detection on mobile robots

As a cell of Flexible Manufacturing System (FMS), Automated Guided Vehicle (AGV) is widely used in factory. In this paper, we presented a novel technology used for vision-guided AGV. An embedded dual-core processor system with Real-Time Operating System (RTOS) DSP/BIOS is designed for system manager and image processor. We adopt DSP TMS320DM642 as image processor and ARM LPC2210 as controller. The embedded RTOS DSP/BIOS is transplanted on DSP to construct a software development platform for tasks management, which enhance reliability and real-time response of system. Two CCD cameras are fixed on vehicle to capture the scene of lane. One, on the front of vehicle, is used for prediction, the other, at the center of vehicle, is used for accurate positioning. Radio Frequency Identification (RFID) reader is loaded on vehicle to collect the information stored in RFID tag which placed by the side of lane. The experimental results demonstrate the advantages of real-time and robust.

A Dual-Core Real-Time Embedded System for Vision-Based Automated Guided Vehicle

Computer Vision Assisted Line Following Robot

Vision-based sensors are a key component for robot systems, where many tasks depend on image data. Realtime constrains of the control tasks bind a lot of processing power only for a single sensor modality. Dedicated and distributed processing resources are the "natural" solution to overcome this limitation. This paper presents first experiments, using embedded processors as well as dedicated hardware, performing various image (pre)processing tasks. Architectural concepts and requirements for smart vision systems have been acquired.

Towards intelligent autonomous vision systems - smart image processing for robotic applications -

Vision-based sensors are a key component for robot-systems, where many tasks depend on image data. Realtime control constraints bind a lot of processing power for only a single sensor modality. Dedicated and distributed processing resources are the "natural" solution to overcome this limitation. This paper presents experiments, using embedded processors as well as dedicated hardware, to execute various image (pre)processing tasks. Architectural concepts and requirements for intelligent vision systems have been acquired.

Intelligent vision systems for robotic applications

A major problem in the area of service robotics is the limitation of the processing capability within the system. Especially vision-based sensors have high demands on realtime control. This paper presents an autonomous subsystem for FireWire cameras which can be adapted to various tasks, ranging from simple control up to image (pre)processing. The system contains an embedded processor as well as dedicated hardware for signal preprocessing realized on a FPGA prototyping board.

http://www.wseas.us/e-library/conferences/2006hangzhou/papers/531-828.pdf

System design for an autonomous smart vision system

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Towards intelligent autonomous vision systems - smart image processing for robotic applications -

Intelligent vision systems for robotic applications

System design for an autonomous smart vision system