External force detection for physical human-robot interaction using dynamic model identification

Dewen Wu*, Quan Liu, Wenjun Xu, Aiming Liu, Zude Zhou, Duc Truong Pham

*Corresponding author for this work

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

2 Citations (Scopus)


Nowadays as more and more tasks require humans to collaborate with robots in modern industry, and the focus of many robotic researchers worldwide has turned towards human-robot collaboration. In human-robot interaction, ensuring the safety issues has the absolute priority for all other research work. In this context, sensorless collision detection and fast response researches in robotics contribute significantly to solve the safety issues. However, existing approaches for collision detection involve in the usage of external sensors, not fit for closed industrial robots or the offline observer based on robot’s the generalized momentum, poor in the real time response. In this study, a different method of external forces detection for sensor-less industrial robots using dynamics model identification is proposed. The main idea of our method is to identify the external torques by the comparison of the actual motor torques with the predicted joint torques based on dynamics model. Without using any extra sensors, a strict dynamics model including the parameterized friction torques has been formulated only by utilizing the measurements of the joint angles and joint torques. In addition, the essential response strategies in the post-contact stage are the main directions for our following research. Finally, the model accuracy and performance of the proposed method were evaluated in a 6-DOF manipulator. The experimental results demonstrated the reliability of our detection method basically.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications
Subtitle of host publication10th International Conference, ICIRA 2017, 17 Wuhan, China, August 16–18, 2017, Proceedings, Part 1
EditorsYongAn Huang, Hao Wu, Honghai Liu, Zhouping Yin
PublisherSpringer Verlag
Number of pages12
ISBN (Electronic)9783319652894
ISBN (Print)9783319652887
Publication statusPublished - 1 Jan 2017
Event10th International Conference on Intelligent Robotics and Applications, ICIRA 2017 - Wuhan, China
Duration: 16 Aug 201718 Aug 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10462 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th International Conference on Intelligent Robotics and Applications, ICIRA 2017


  • Dynamics model identification
  • External force detection
  • Physical human-robot interaction
  • Safety-aware

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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