Zhiyuan Cai - IEEE Xplore Author Profile

Scheduled Maintenance on Monday 1/13/2025

Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Access provided by:

MIT Libraries

Access provided by:

MIT Libraries

ADVANCED SEARCH

Author details

Zhiyuan Cai

Publications

6

Citations

17

Publications by Year

20222025

Co-Authors:

Huanhui CaoWeipeng CaoPujin ChengYuhong FengJiongjiong Gu

Show All Co-Authors (23)

Zhiyuan Cai

Affiliation

Huawei Cloud Computing Technologies Company Ltd., Shenzhen, China

Publication Topics

Fundus Images,
Self-supervised Learning,
Feature Fusion,
Medical Imaging,
Optical Coherence Tomography Images,
Vision Transformer,
2D Images,
3D Images,
3D Volume,
Active Users,
Actor Network,
Adaptive Model

Biography

Zhiyuan Cai a chief engineer with Huawei Cloud, is active in the OpenStack open source community and served as a core member and PTL of the Tricircle project. He also participated in the incubation of IEF cloud services. Currently, he focuses on improving the utilization of cloud resources and ensuring the QoS of service performance.(Based on document published on 31 October 2024).

Publications

6

Citations

17

Publications by Year

20222025

Co-Authors:

Huanhui Cao
Weipeng Cao
Pujin Cheng
Yuhong Feng
Jiongjiong Gu

Show All Co-Authors (23)

Author's Published Works

Search History

Showing 1-4 of 4 results

Conferences (2)

Journals (2)

Sort

Filter Results

Show

Open Access Only

Range
Single Year
Dongjun Lee(4)
ChangU Kim(3)
Bukun Son(2)
Jihyun Moon(2)
Minhyeong Lee(2)
Department of Mechanical Engineering, IAMD and IOER, Seoul National University, Seoul, South Korea(1)
HD Hyundai XiteSolution, Gyeonggi-do, South Korea(1)
Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, Korea(1)
Doosan Infracoore, Seoul, South Koera(1)
Department of Mechanical Engineering, IAMD and IER, Seoul National University, Seoul, South Korea(1)
IEEE Robotics and Automation Letters(2)
2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)(1)
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(1)
IEEE(4)
Media(3)
Goyangi, Korea (South)(1)
Las Vegas, NV, USA(1)
Inertial Measurement Unit(3)
Data-driven Models(2)
Inertial Frame(2)
Multilayer Perceptron(2)
Neural Network(2)

Select All on Page

Sort By

Results

Real-Time Excavation Trajectory Modulation for Slip and Rollover Prevention

ChangU Kim;Bukun Son;Minhyeong Lee;Hyelim Choi;Seokhyun Hong;Minsung Kang;Jihyun Moon;Dongmok Kim;Dongjun Lee

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

HTML

We propose a novel real-time excavation trajectory modulation framework on a slope for an autonomous excavator with a low-level digital kinematic control as common for hydraulic industrial excavators. Excavation on a slope is challenging because of a higher risk of slips and rollovers. To deal with this, we propose a real-time excavation trajectory modulation framework based on slope tangential/no...Show More

Real-Time Excavation Trajectory Modulation for Slip and Rollover Prevention

ChangU Kim;Bukun Son;Minhyeong Lee;Hyelim Choi;Seokhyun Hong;Minsung Kang;Jihyun Moon;Dongmok Kim;Dongjun Lee

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

Precision Motion Control of Robotized Industrial Hydraulic Excavators via Data-Driven Model Inversion

Minhyeong Lee;Hyelim Choi;ChangU Kim;Jihyun Moon;Dongmok Kim;Dongjun Lee

IEEE Robotics and Automation Letters

Year: 2022 | Volume: 7, Issue: 2 | Journal Article |

Cited by: Papers (25)

HTML

This work proposes a novel precision motion control framework of robotized industrial hydraulic excavators via data-driven model inversion. Rather than employing a single neural network to approximate the whole excavator dynamics, including input delays and dead-zones, we construct a physics-inspired data-driven model with a modular structure. The data-driven model is then inverted in a modular fa...Show More

Precision Motion Control of Robotized Industrial Hydraulic Excavators via Data-Driven Model Inversion

Minhyeong Lee;Hyelim Choi;ChangU Kim;Jihyun Moon;Dongmok Kim;Dongjun Lee

IEEE Robotics and Automation Letters

Year: 2022 | Volume: 7, Issue: 2 | Journal Article |

Expert-Emulating Excavation Trajectory Planning for Autonomous Robotic Industrial Excavator

Bukun Son;ChangU Kim;Changmuk Kim;Dongjun Lee

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2020 | Conference Paper |

Cited by: Papers (20)

HTML

We propose a novel excavation (i.e., digging) trajectory planning framework for industrial autonomous robotic excavators, which emulates the strategies of human expert operators to optimize the excavation of (complex/unmodellable) soils while also upholding robustness and safety in practice. First, we encode the trajectory with dynamic movement primitives (DMP), which is known to robustly preserve...Show More

Expert-Emulating Excavation Trajectory Planning for Autonomous Robotic Industrial Excavator

Bukun Son;ChangU Kim;Changmuk Kim;Dongjun Lee

2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2020 | Conference Paper |

2-D cooperative localization with omni-directional mobile robots

Changu Kim;Hyunsoo Yang;Dongho Kang;Dongjun Lee

2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

Year: 2015 | Conference Paper |

Cited by: Papers (4)

HTML

In this paper, we propose cooperative localization scheme based feedback control for the multiple omni-directional mobile robots. Using the proposed cooperative localization scheme, localization capability of each mobile robot is enhanced, although some of the robots loss its absolute position measurement. Position error is bounded based on relative measurements which is unbounded for dead reckoni...Show More

2-D cooperative localization with omni-directional mobile robots

Changu Kim;Hyunsoo Yang;Dongho Kang;Dongjun Lee

2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

Year: 2015 | Conference Paper |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Test Whats new message.