Adaptation-and-collision detection scheme for safe physical human-robot interaction

Chang Nho Cho, Young Loul Kim, Jae Bok Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)


Human-robot collisions are unavoidable during a human-robot interaction. Thus, a number of collision detection algorithms have been proposed to ensure human safety during such an occasion. However, collision detection algorithms are usually model-based, requiring an accurate model of the robot. The errors in the model can lead to the malfunction of the algorithms. In this study, we propose an adaptation and collision detection scheme to improve the sensitivity of the collision detection algorithm. Performing adaptation prior to collision detection will effectively minimize the model uncertainty of the robot. This minimization will allow sensitive, reliable collision detection. By using torque filtering, adaptation and collision detection can be done without the need for the acceleration estimation. The performance of the proposed scheme is demonstrated by various experiments.

Original languageEnglish
Title of host publication2013 9th Asian Control Conference, ASCC 2013
Publication statusPublished - 2013
Event2013 9th Asian Control Conference, ASCC 2013 - Istanbul, Turkey
Duration: 2013 Jun 232013 Jun 26

Publication series

Name2013 9th Asian Control Conference, ASCC 2013


Other2013 9th Asian Control Conference, ASCC 2013


  • Adaptive control
  • Collision detection
  • Collision safety

ASJC Scopus subject areas

  • Control and Systems Engineering


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