Prediction of Human Trajectory following a Haptic Robotic Guide Using Recurrent Neural Networks

Hee Seung Moon, Jiwon Seo

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

1 Citation (Scopus)

Abstract

Social intelligence is an important requirement for enabling robots to collaborate with people. In particular, human path prediction is an essential capability for robots in that it prevents potential collision with a human and allows the robot to safely make larger movements. In this paper, we present a method for predicting the trajectory of a human who follows a haptic robotic guide without using sight, which is valuable for assistive robots that aid the visually impaired. We apply a deep learning method based on recurrent neural networks using multimodal data: (1) human trajectory, (2) movement of the robotic guide, (3) haptic input data measured from the physical interaction between the human and the robot, (4) human depth data. We collected actual human trajectory and multimodal response data through indoor experiments. Our model outperformed the baseline result while using only the robot data with the observed human trajectory, and it shows even better results when using additional haptic and depth data.

Original languageEnglish
Title of host publication2019 IEEE World Haptics Conference, WHC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages157-162
Number of pages6
ISBN (Electronic)9781538694619
DOIs
Publication statusPublished - 2019 Jul
Event2019 IEEE World Haptics Conference, WHC 2019 - Tokyo, Japan
Duration: 2019 Jul 92019 Jul 12

Publication series

Name2019 IEEE World Haptics Conference, WHC 2019

Conference

Conference2019 IEEE World Haptics Conference, WHC 2019
CountryJapan
CityTokyo
Period19/7/919/7/12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Biomedical Engineering
  • Sensory Systems
  • Human Factors and Ergonomics

Fingerprint Dive into the research topics of 'Prediction of Human Trajectory following a Haptic Robotic Guide Using Recurrent Neural Networks'. Together they form a unique fingerprint.

  • Cite this

    Moon, H. S., & Seo, J. (2019). Prediction of Human Trajectory following a Haptic Robotic Guide Using Recurrent Neural Networks. In 2019 IEEE World Haptics Conference, WHC 2019 (pp. 157-162). [8816157] (2019 IEEE World Haptics Conference, WHC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WHC.2019.8816157