Collision detection algorithm to distinguish between intended contact and unexpected collision

Chang Nho Cho, Joon Hong Kim, Young Loul Kim, Jae Bok Song, Jin Ho Kyung

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

Industrial and service robots often physically interact with humans, and thus, human safety during these interactions becomes significantly important. Several solutions have been proposed to guarantee human safety, and one of the most practical, efficient solutions is the collision detection using generalized momentum and joint torque sensors. This method allows a robot to detect a collision and react to it as soon as possible to minimize the impact. However, the conventional collision detection methods cannot distinguish between intended contacts and unexpected collisions, and thus they cannot be used during certain tasks such as teaching and playback or force control. In this paper, we propose a novel collision detection algorithm which can distinguish intended contacts and unexpected collisions. In most cases, the external force during a collision shows a noticeably faster rate of change than that during an intended contact, and using this difference, the proposed observer can distinguish one from the other. Several experiments were conducted to show that the proposed algorithm can effectively distinguish intended contacts and unexpected collisions.

Original languageEnglish
Pages (from-to)1825-1840
Number of pages16
JournalAdvanced Robotics
Volume26
Issue number16
DOIs
Publication statusPublished - 2012 Nov 1

Keywords

  • collision detection
  • force control
  • human safety
  • joint torque sensors
  • teaching and playback

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Collision detection algorithm to distinguish between intended contact and unexpected collision'. Together they form a unique fingerprint.

Cite this