Hello there! I am a second-year PHD student in HKU(the University of HongKong), advised by Prof. Ping Luo. I am currently intern in Shanghai AI Lab, supervised by Dr. Jiangmiao Pang. I obtained my Master and B.Eng. degree in Tsinghua University under the supervision of Prof. Guijin Wang.

I am currently working on humanoid robots whole-body control. If you are interested in my research or want to chat, please drop me an email.

Junli Ren「任峻立」

Humanoid Goalkeeper learns a single end-to-end RL policy, executing agile, human-like motions to intercept flying balls, as well as performing tasks such as escaping a ball using jump and squat motions.

we introduce AdaMimic, a novel motion tracking algorithm that enables adaptable humanoid control from a single reference motion.

We present a physical-world humanoid-scene interaction system, PhysHSI, that enables humanoids to autonomously perform diverse interaction tasks while maintaining natural and lifelike behaviors.

We propose VB-Com, a composite framework that enables humanoid robots to determine when to rely on the vision policy and when to switch to the blind policy under perceptual deficiency.

we present HoST (Humanoid Standing-up Control), a reinforcement learning framework that learns standing-up control from scratch, enabling robust sim-to-real transfer across diverse postures.

BeamDojo achieves efficient learning in simulation and enables agile locomotion with precise foot placement on sparse footholds in the real world, maintaining a high success rate even under significant external disturbances.

We propose the Perceptive Intenal Model (PIM), a method to estimate environmental disturbances with perceptive information, enabling agile and robust locomotion for various humanoid robots on various terrains.

We propose TOP-Nav, a novel legged navigation framework that integrates a comprehensive path planner with Terrain awareness, Obstacle avoidance and close-loop Proprioception.

Updated at Feb. 2025.
Template from Jon Barron.