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Related Concept Videos

PD Controller: Design01:26

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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
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Design and Characterization of a Powered Wheelchair Autonomous Guidance System.

Vincenzo Gallo1, Irida Shallari2, Marco Carratù1

  • 1Department of Industrial Engineering, University of Salerno, 84084 Fisciano, Italy.

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Summary

This study introduces a new method using a monocular RGB camera to measure caregiver distance for powered wheelchairs (PWs). The lightweight system achieves accuracy comparable to LiDAR, enhancing wheelchair navigation and user autonomy.

Keywords:
deep neural networkdistance measurement methodologymetrological characterizationpowered wheelchair

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Area of Science:

  • Robotics
  • Computer Vision
  • Machine Learning

Background:

  • Advancements in machine learning are driving innovations in assistive technologies like autonomous and semiautonomous Powered Wheelchairs (PWs).
  • Existing systems often require complex hardware and calibration, limiting widespread adoption.
  • There is a need for lightweight, accurate, and easily deployable navigation systems for PWs.

Purpose of the Study:

  • To design and validate a lightweight, real-time measurement methodology for estimating caregiver distance from a Powered Wheelchair (PW).
  • To enable embedded implementation of an accurate navigation system for enhanced user autonomy.
  • To compare the metrological performance of the proposed 2D imaging method with existing 3D depth sensing technologies.

Main Methods:

  • Development of a real-time measurement methodology utilizing a monocular RGB camera.
  • Application of a deep learning model for caregiver foot detection.
  • Distance estimation from the PW to the detected caregiver.
  • Metrological characterization and comparison with depth cameras (e.g., LiDAR, stereo cameras).

Main Results:

  • The proposed monocular RGB camera-based method achieves metrological performance comparable to Light Detection and Ranging (LiDAR) and stereo cameras.
  • Measurement uncertainties were within a magnitude of 10 cm.
  • Significant reduction in data volume and object detection complexity was observed.
  • Reduced complexity in calibration, positioning, and deployment compared to 3D segmentation algorithms.

Conclusions:

  • The developed methodology offers a viable, lightweight, and accurate alternative for caregiver distance estimation in PW navigation.
  • The system facilitates easier deployment and integration into PWs due to reduced complexity.
  • This approach enhances the autonomy of PW users by improving guidance and environmental interaction capabilities.