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Updated: Jan 28, 2026

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Collision Detection and Identification on Robot Manipulators Based on Vibration Analysis.

Feiyan Min1,2, Gao Wang3,4, Ning Liu5,6

  • 1Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, China. minfeiyan@aliyun.com.

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|March 6, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a novel, model-independent collision detection method for robot manipulators using vibration features. The approach accurately identifies collisions, their location, and direction, minimizing damage.

Keywords:
artificial neural networkcollision detectioncollision identificationmanipulatormodel independent methodvibration analysis

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Area of Science:

  • Robotics
  • Mechanical Engineering
  • Artificial Intelligence

Background:

  • Robot manipulators require rapid collision detection to prevent damage.
  • Existing model-based methods often rely on torque differences, which can be imprecise.
  • A need exists for robust, model-independent collision detection strategies.

Purpose of the Study:

  • To present a model-independent collision detection method for robot manipulators.
  • To utilize vibration features generated during collisions for detection.
  • To determine the location and direction of collisions.

Main Methods:

  • Extraction of natural frequencies and vibration modal features during collisions.
  • Development of a peak frequency-based method for vibration modal estimation.
  • Construction and training of an artificial neural network using vibration modal features.

Main Results:

  • The proposed method effectively detects collisions in robot manipulators.
  • The artificial neural network accurately identifies collision location and direction.
  • Experimental validation confirms the scheme's considerable accuracy.

Conclusions:

  • Vibration modal features provide a viable basis for model-independent collision detection.
  • The developed artificial neural network-based approach offers a robust solution.
  • This method enhances robot safety and damage limitation capabilities.