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20242026
most citedHybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response

4 citations · 7 across the 9 of their papers we have counts for

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Showing 2024 · cs.ROShow all

5 papers · 2 filters

cs.RO2024

Learning Humanoid Locomotion with Perceptive Internal Model

Junfeng Long, Junli Ren, Moji Shi +4

In contrast to quadruped robots that can navigate diverse terrains using a "blind" policy, humanoid robots require accurate perception for stable locomotion due to their high degre…

cs.RO2024

GRUtopia: Dream General Robots in a City at Scale

Hanqing Wang, Jiahe Chen, Wensi Huang +19

Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Rea…

cs.RO2024★ 1 cited

TOP-Nav: Legged Navigation Integrating Terrain, Obstacle and Proprioception Estimation

Junli Ren, Yikai Liu, Yingru Dai +2

Legged navigation is typically examined within open-world, off-road, and challenging environments. In these scenarios, estimating external disturbances requires a complex synthesis…

cs.RO2024★ 1 cited

Learning H-Infinity Locomotion Control

Junfeng Long, Wenye Yu, Quanyi Li +3

Stable locomotion in precipitous environments is an essential task for quadruped robots, requiring the ability to resist various external disturbances. Recent neural policies enhan…

cs.RO2024★ 4 cited

Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response

Junfeng Long, Zirui Wang, Quanyi Li +3

Robust locomotion control depends on accurate state estimations. However, the sensors of most legged robots can only provide partial and noisy observations, making the estimation p…