Jiajun Yu - 余佳骏

Hi! I am currently pursuing a master’s degree in the FastLab (Fire Group) at the College of Control Science and Engineering, Zhejiang University, under the guidance of Yanjun Cao and Chao Xu. If you’re interested in discussing my work or potential collaborations, feel free to email me at jjyu@zju.edu.cn.

Education

  • Zhejiang University, M.S. in Control Science and Engineering, 2024.09 - 2027.06
    • FastLab (Fire Group) | Research Focus: Trajectory Planning & Optimization, Reinforcement Learning, End-to-End Autonomous Navigation
    • Honors: Outstanding Graduate Student of Zhejiang University (2024-2025); Outstanding Graduate Student of ZJU Huzhou Institute (2025)
  • Harbin Institute of Technology, B.E. in Robotics Engineering, 2020.09 - 2024.06
    • GPA: 93.13/100 | Rank: 5/298
    • Honors: National Scholarship; First Prize in National Intelligent Car Competition; SMC First-Class Scholarship

Research Interests

My research focuses on parallel trajectory optimization for robotics, which has demonstrated strong performance in large-scale and long-horizon problems. I design GPU-accelerated algorithms that harness modern computing architectures for maximum efficiency. Currently, I am actively exploring the integration of machine learning methods with traditional optimization techniques to further accelerate the trajectory optimization process and uncover new potential from this synergy.

  • Trajectory Planning & Optimization
  • Parallel Trajectory Optimization
  • Deep Reinforcement Learning
  • End-to-End Autonomous Navigation

Publications

1. TOP: Trajectory Optimization via Parallel Optimization towards Constant Time Complexity

  • Authors: Jiajun Yu†, Nanhe Chen†, Guodong Liu, Chao Xu, Fei Gao, and Yanjun Cao
  • Venue: IEEE Robotics and Automation Letters, 2025 (Presented at ICRA 2026)
  • Links: PaperVideo
  • Status: ✓ Accepted
TOP Algorithm Video Thumbnail
点击播放
Trajectory optimization demonstration - Click to play

Projects

1. Air-Ground Cooperation without Global Information: RoFly and CubeTrack Cooperation with CREPES and CoNi-MPC

  • Authors: Jiajun Yu, Jiadong Lu, Li Wang, Mingxuan Zhang, Pengxiang Zhou, Ruitian Pang, Xiangyu Li, Zhehan Li, Chao Xu, and Yanjun Cao
  • Venue: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) EXPO, 2025
  • Links: Project Page

IROS 2025 EXPO

2. Autonomous UAV Inspection System for Power Substations

  • Role: Planning & Control Lead · Enterprise Collaboration Project
  • Developed a micro UAV (<800g, >15min endurance) autonomous inspection system for complex indoor substation environments; implemented GPS-denied real-time visual localization via onboard ORB-SLAM; equipped with thermal and RGB cameras for equipment temperature monitoring and instrument reading detection; achieved full-coverage path planning with interest-point-guided global coverage and local obstacle-avoidance trajectory optimization; successfully deployed and tested on-site.

Ongoing Works

1. Learning Safety-enhanced Navigation with Integrated Model Information

  • Authors: Nanhe Chen†, Jiajun Yu†, Mengke Zhang†, Pengxiang Zhou, Chao Xu, Fei Gao, and Yanjun Cao
  • Target Venue: IEEE Transactions on Robotics, 2026
  • Links: PaperVideo
  • Status: 📝 To be Submitted

2. ATRS: Adaptive Trajectory Re-splitting via a Shared Neural Policy for Parallel Optimization

  • Authors: Jiajun Yu, Guodong Liu, Chao Xu, Fei Gao, and Yanjun Cao
  • Target Venue: IEEE Robotics and Automation Letters, 2026
  • Links: PaperVideo
  • Status: 📝 To be Submitted

3. Whole-body Planning for Any-Shape Robot directly in Point Cloud

  • Authors: Guodong Liu†, Jiajun Yu†, Chao Xu, Fei Gao, and Yanjun Cao
  • Target Venue: IEEE Robotics and Automation Letters, 2026
  • Links: PaperVideo
  • Status: 📝 To be Submitted

4. CoNiPA: Cooperative Non-inertial Control Framework with LSTM-Enhanced Predictive Awareness

  • Authors: Mingxuan Zhang†, Jiajun Yu†, Baozhe Zhang†, Chao Xu, Fei Gao, and Yanjun Cao
  • Target Venue: IEEE Robotics and Automation Letters, 2026
  • Links: PaperVideo
  • Status: 📝 To be Submitted