Junli Ren「任峻立」

The first ego-centric humanoid table tennis player, as well as agile smash behaviors.

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 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 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 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 April. 2026.
Template from Jon Barron.