Handing over Objects to Human in a Friendly and Comfortable Manner

Biyun Xie, Jing Zhao

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In this paper, a robotic motion planning scheme is proposed to generate hand-over motions in a friendly and comfortable manner. Two sub-problems are studied: The determination of the final target position (where the robot should hand over the object to) and the generation of human-like motion in the hand-over process (how the robot should hand over the object to the position). First, experiments of different subjects are conducted to explore the common characteristics in the optimal hand-over positions. The result shows that their joint angles are similar at the optimal hand-over position. Therefore, the optimal hand-over position can be determined by forward kinematics based on the measured average joint angles. Then, two methods are proposed to plan the human-like hand-over motions in an obstacle-free environment and in an obstacle-present environment, respectively. A series of experimental comparisons is conducted to prove the validity of the methods. A robotic arm is controlled to hand over a cube to humans in human-like way and nonhuman-like way. The subjects are asked to grade the hand-over motion of the robotic arm on a scale of 1 to 5. The results show that the hand-over motions planned by the methods proposed in this paper can make people feel safer and more comfortable.

Original languageEnglish
Article number1550012
JournalInternational Journal of Humanoid Robotics
Volume12
Issue number4
DOIs
StatePublished - Dec 1 2015

Bibliographical note

Funding Information:
This research is supported by National Natural Science Foundation of China (No. 51475016) and by Doctoral Fund of Innovation of Beijing University of Technology (No.YB201303).

Publisher Copyright:
© 2015 World Scientific Publishing Company.

Keywords

  • Human-robot interaction
  • hand-over motion
  • motion planning of human-like movement
  • object hand-over position

ASJC Scopus subject areas

  • Mechanical Engineering
  • Artificial Intelligence

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