Collision detection algorithm robust to model uncertainty

Chang Nho Ho, Jae Bok Song

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


With the widespread use of service robots, safety issues regarding human-robot collisions have received increasing attention. The collision detection algorithm, which allows a robot to effectively detect and react against a collision, is considered as one of the most practical solutions for ensuring collision safety. However, these algorithms are often model-based, so it cannot ensure collision safety under payload variations or model uncertainty. In this paper, a novel collision detection algorithm based on torque filtering is proposed to cope with this problem. The torque due to the motion of the robot can be effectively removed using the Butterworth 2nd-order BPF (band pass filter) so that only the torque due to a collision is used for collision detection. This improves the robustness of the algorithm against model uncertainties. The proposed algorithm does not require the use of acceleration data. The performance of the algorithm was experimentally verified.

Original languageEnglish
Pages (from-to)776-781
Number of pages6
JournalInternational Journal of Control, Automation and Systems
Issue number4
Publication statusPublished - 2013 Aug

Bibliographical note

Funding Information:
This work was supported by the Human Resources Development Program for Convergence Robot Specialists and by Korea University Research Fund.


  • Band pass filter
  • collision detection
  • collision safety
  • torque filtering

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications


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