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Machines01:19

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
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Related Experiment Video

Updated: Jul 19, 2026

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
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Adaptive FPGA-Based Accelerators for Human-Robot Interaction in Indoor Environments.

Mangali Sravanthi1,2, Sravan Kumar Gunturi1, Mangali Chinna Chinnaiah3,4

  • 1Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Aziznagar, Hyderabad 500075, Telangana, India.

Sensors (Basel, Switzerland)
|November 9, 2024
PubMed
Summary

This study enhances human-robot interaction using adaptive field-programmable gate array (FPGA) accelerators for real-time indoor localization and service delivery. The system accurately predicts human posture and robot intentions, improving navigation in confined spaces.

Keywords:
FPGAlocalizationposture recognitionsensor fusionservice robot

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Engineering

Background:

  • Human-robot interaction (HRI) in real-time indoor environments presents challenges for service robots, particularly in predicting human posture and location.
  • Accurate human localization and understanding robot intentions are crucial for seamless service delivery in confined spaces.

Purpose of the Study:

  • To develop an adaptive FPGA-based system for real-time human localization and robot intention estimation in indoor environments.
  • To enhance human-robot implicit communication and navigation capabilities for service robots.

Main Methods:

  • Utilized sensor fusion with PIR and ultrasonic sensors for binary classification of static and adaptive human postures.
  • Implemented adaptive Simultaneous Localization and Mapping (SLAM) for robot task delivery and navigation.
  • Developed VLSI hardware schemes and Verilog HDL for algorithm implementation and FPGA synthesis.

Main Results:

  • Successfully demonstrated real-time human posture analysis and localization using sensor fusion.
  • Validated the adaptive SLAM-based triangulation navigation method for robot service delivery.
  • Experimental validation conducted in a hospital environment using a Zed-board-based FPGA Xilinx board.

Conclusions:

  • The proposed FPGA-accelerated approach effectively addresses real-time human localization and robot intention prediction challenges in HRI.
  • The developed methodologies enable adaptive navigation and implicit communication for service robots in complex indoor settings.
  • The system's performance was validated in a realistic hospital environment, showcasing its practical applicability.