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PD Controller: Design01:26

PD Controller: Design

167
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,...
167

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Design and Implementation of an Interactive System for Service Robot Control and Monitoring.

Jonas Machado Santana1, Bruno Duarte Silveira1, Crescencio Lima1

  • 1GIPAR Research Group, Instituto Federal da Bahia, IFBA, Vitória da Conquista, Bahia 45078-900, Brazil.

Sensors (Basel, Switzerland)
|February 26, 2025
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Summary
This summary is machine-generated.

This study introduces an interactive control system for autonomous wheelchairs using ROS and Google Gemini. It personalizes navigation through user preferences, facial recognition, and chatbot interaction, enhancing user autonomy and quality of life.

Keywords:
chatbotinteractionrecognitionroboticsservice robotsystem

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Area of Science:

  • Robotics and Human-Computer Interaction
  • Artificial Intelligence and Machine Learning

Background:

  • Autonomous service robots require intuitive control systems for personalized user experiences.
  • Existing systems often lack adaptive capabilities and deep user integration.

Purpose of the Study:

  • To develop an interactive control system for autonomous service robots, specifically a motorized wheelchair.
  • To enhance user control and personalization through a web interface and AI-powered chatbot.
  • To improve the autonomy and quality of life for wheelchair users.

Main Methods:

  • Integration of Robot Operating System (ROS) for robot control.
  • Development of a web interface and an interactive chatbot utilizing Google Gemini.
  • Implementation of an API for accessing a user preference database.
  • Incorporation of facial recognition and adaptive chatbot responses for personalized navigation.

Main Results:

  • The system successfully adjusted wheelchair behavior to user preferences, enhancing safety and personalization.
  • Facial recognition and chatbot interaction led to more intuitive and efficient control.
  • The developed system demonstrated significant improvements in user autonomy and quality of life.

Conclusions:

  • The integration of ROS, web interfaces, and AI chatbots offers a transformative approach to autonomous wheelchair control.
  • The system provides a viable and efficient solution for personalized autonomous navigation, meeting specific user needs.
  • This technology has the potential to significantly improve the daily lives of individuals requiring mobility assistance.