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A low cost matching motion estimation sensor based on the NIOS II microprocessor.

Diego González1, Guillermo Botella, Uwe Meyer-Baese

  • 1Department of Computer Architecture and Automation, Complutense University of Madrid, Madrid 28040, Spain. dgonzalez@grupobme.es

Sensors (Basel, Switzerland)
|December 4, 2012
PubMed
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This study implements a low-cost motion estimation sensor using Field Programmable Gate Arrays (FPGA) and C to Hardware (C2H) acceleration for real-time robotic applications.

Area of Science:

  • Robotics and Embedded Systems
  • Computer Engineering
  • VLSI Design

Background:

  • Motion estimation is crucial for real-time robotic applications like tracking and navigation.
  • Existing solutions often face limitations in terms of cost, power consumption, or real-time processing capabilities.
  • Field Programmable Gate Arrays (FPGAs) offer a flexible platform for hardware acceleration.

Purpose of the Study:

  • To implement and evaluate a matching-based motion estimation sensor on an FPGA.
  • To leverage C to Hardware (C2H) acceleration for optimizing the design.
  • To analyze the resource utilization and throughput of the developed system.

Main Methods:

  • Implementation of matching algorithms on an FPGA using Very Large Scale Integration (VLSI) technology.

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  • Utilizing a NIOS II microprocessor for system integration.
  • Employing a C to Hardware (C2H) acceleration paradigm for design optimization.

    • Main Results:

    • Successful hardware implementation of a matching-based motion estimation sensor.
    • Demonstrated practical real-time throughput and reduced power consumption.
    • Extensive analysis of resource requirements and system performance.

    Conclusions:

    • The developed FPGA-based motion estimation system is a cost-effective solution for real-time robotic applications.
    • The C2H acceleration paradigm effectively optimizes the hardware implementation for improved performance.
    • The system is suitable for tasks such as object tracking and unmanned vehicle navigation.