1. Home
  2. Honda R&D Technical Review Vol.33 N...
  3. Research of Robust Follower Recogni...

Technical Review e-Book: Summary

Research of Robust Follower Recognition Function for Airport Guide Robot

Article of Honda R&D Technical Review Vol.33 No.1

Summary

Hospitality is a key factor for the success of guide robot service. This paper defines a new recognition function called follower recognition, and proposes a hybrid approach to realize the follower recognition function. This approach creates a fusion of facial recognition, human body tracking, and person re-identification algorithms and takes advantage of the respective technological characteristics to realize robust follower recognition against issues such as recognition distance change, illumination change, and occlusion from the robot’s perspective. The proving test result at Narita International Airport showed that the proposed approach is practical in guide robot service.

Reference

(1) Velentza, A.-M., Heinke, D., Wyatt, J.: Human Interaction and Improving Knowledge through Collaborative Tour Guide Robots, 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), p. 1-7, (2019)
(2) Saito, Y., Koshiishi, T.:Development and Styling Design of Airport Guide Robot System, Honda R&D Technical Review, Vol. 33, No. 1, p. 1-9
(3) Onishi, J., Masuda, A., Obayashi, C., Kawasaki, Y., Takebe, Y.: Development of Reception Robot for Airport Guidance, Honda R&D Technical Review, Vol. 33, No. 1, p. 10-18
(4) https://talorongilad.com/research-laboratories/follow-me-design-for-person-following-robots/, 2021/01/19
(5) Azarbayejani, A., Pentland, A.: Real-Time Self-Calibrating Stereo Person Tracking Using 3-D Shape Estimation from Blob Features, Proceedings of 13th International Conference on Pattern Recognition, Vol. 3, p. 627-632, (1996)
(6) Wren, C. R., Azarbayejani, A., Darrell, T., Pentland, A. P.: Pfinder: Real-Time Tracking of the Human Body, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, p. 780-785, (1997)
(7) Darrell, T., Gordon, G., Harville, M., Woodfill, J.: Integrated Person Tracking using Stereo, Color, and Pattern Detection, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), p. 601-608, (1998)
(8) Pierre, J. M.: End-to-End Deep Learning for Robotic Following, Proceedings of the 2018 2nd International Conference on Mechatronics Systems and Control Engineering, p. 77-85, (2018)
(9) Chen, B. X., Sahdev, R., Tsotsos, J. K.: Person Following Robot Using Selected Online Ada-Boosting with Stereo Camera, 2017 14th Conference on Computer and Robot Vision (CRV), p. 48-55, (2017)
(10) Wang, M., Su, D., Shi, L., Liu, Y., Miro, J. V.: Real-time 3D human tracking for mobile robots with multisensors, 2017 IEEE International Conference on Robotics and Automation (ICRA), p. 5081-5087, (2017)
(11) Leigh, A., Pineau, J., Olmedo, N., Zhang, H.: Person Tracking and Following with 2D Laser Scanners, 2015 IEEE International Conference on Robotics and Automation (ICRA), p. 726-733, (2015)
(12) Peng, W., Wang, J., Chen, W.: Tracking Control of Human-Following Robot with Sonar Sensors, International Conference on Intelligent Autonomous Systems, p. 301-313, (2017)
(13) Germa, T., Lerasle, F., Ouadah, N., Cadenat, V.: Vision and RFID Data Fusion for Tracking People in Crowds by a Mobile Robot, Computer Vision and Image Understanding, p. 641-651, (2010)
(14) Gou, M., Karanam, S., Liu, W., Camps, O., Radke, R. J.: DukeMTMC4ReID: A Large-Scale Multi-Camera Person Re-Identification Dataset (Open Access version), 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, p. 10-19, (2017)
(15) Sha, Z., Zeng, Z., Wang, Z., Natori, Y., Taniguchi, Y., Satoh, S.: Progressive Domain Adaptation for Robot Vision Person Re-identification, MM ’20: Proceedings of the 28th ACM International Conference on Multimedia, p. 4488-4490, (2020)
(16) Chen, J., Chen, J., Wang, Z., Liang, C., Lin, C.-W.: Identity-Aware Face Super-Resolution for Low-Resolution Face Recognition, IEEE Signal Processing Letters, Vol. 27, p. 645-649, (2020)
(17) Yuan, J., Chen, H., Sun, F., Huang, Y.: Multisensor information fusion for people tracking with a mobile robot: A particle filtering approach, IEEE Trans. Instrumentation and Measurement, Vol. 64, No. 9, p. 2427-2442, (2015)
(18) Ruan, W., Liu, W., Bao, Q., Chen, J., Cheng, Y., Mei, T.: POINet: Pose-Guided Ovonic Insight Network for Multi-Person Pose Tracking, Proceedings of the 27th ACM International Conference on Multimedia, p. 284-292, (2019)
(19) https://www.narita-airport.jp/en/map?terminal=1&map=3, 2021/01/12

Author (organization or company)

Zijun SHA(Life Creation Center)、Yoichi NATORI(Life Creation Center)、Takahiro ARIIZUMI(Life Creation Center)

We would like to get your opinion on this research paper. (This is only applicable to registered members.)

The readers of this research paper have also selected these research papers.

Development and Styling Design of Airport Guide Robot System
Article of Honda R&D Technical Review Vol.33 No.1
Development of Reception Robot for Airport Guidance
Article of Honda R&D Technical Review Vol.33 No.1
Active Sound Control Technology for Electrified Vehicles Based on Concept of Shepard Tones
Article of Honda R&D Technical Review Vol.33 No.1