王纪龙 | Ji Long (Jaylon) Wang

I am a researcher at Peking University - GALBOT Joint Lab and Center on Frontiers of Computing Studies (CFCS), directed by He Wang. I received my B.S. in Computer Engineering from UC Santa Cruz. I have previously interned at BAAI, SenseTime, Westlake University, and Tsinghua University, and have also participated in exchange programs at UC Berkeley and Shanghai Jiao Tong University.

My research interests lie at the intersection of robotics and machine learning, with a specific focus on locomotion and manipulation tasks. Regarding the “RL vs. MPC” debate, I believe the distinction is subtle, as both methods are fundamentally built through human-in-the-loop processes. A more critical question is how to minimize human involvement while scaling these systems, inspired by Marc Raibert.

Publications

  1. 2024-quadwbg.gif
    QuadWBG: Generalizable Quadrupedal Whole-Body Grasping
    Jilong Wang*, Javokhirbek Rajabov*, Chaoyi Xu, Yiming Zheng, and He Wang
    Under Review
  2. 2024-icra-gamma.gif
    GAMMA: Graspability-Aware Mobile MAnipulation Policy Learning based on Online Grasping Pose Fusion
    Jiazhao Zhang*, Nandiraju Gireesh*Jilong Wang, Xiaomeng Fang, Chaoyi Xu, Weiguang Chen, Liu Dai, and He Wang
    ICRA 2024
  3. 2023-RAS-adaptive.jpg
    Adaptive legged manipulation: Versatile disturbance predictive control for quadruped robots with robotic arms
    Qingfeng Yao, Cong Wang, Jilong Wang, Linghan Meng, Shuyu Yang, Qifeng Zhang, and Donglin Wang
    Robotics and Autonomous Systems
  4. 2022-nips-trifinger.jpg
    Real Robot Challenge: A Robotics Competition in the Cloud
    Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, and 33 more authors
    NeurIPS 2021 Competitions Track
  5. 2021-iros-TA.jpg
    Terrain-Aware Risk-Assessment-Network-Aided Deep Reinforcement Learning for Quadrupedal Locomotion in Tough Terrain
    Hongyin Zhang, Jilong Wang, Zhengqing Wu, Yinuo Wang, and Donglin Wang
    IROS 2021
  6. 2021-iros-HTC.png
    Hierarchical terrain-aware control for quadrupedal locomotion by combining deep reinforcement learning and optimal control
    Qingfeng Yao*Jilong Wang*, Donglin Wang, Shuyu Yang, Hongyin Zhang, Yinuo Wang, and Zhengqing Wu
    IROS 2021