4 citations · 6 across the 3 of their papers we have counts for
4 papers
GLEAM: Learning Generalizable Exploration Policy for Active Mapping in Complex 3D Indoor Scenes
Xiao Chen, Tai Wang, Quanyi Li +3
Generalizable active mapping in complex unknown environments remains a critical challenge for mobile robots. Existing methods, constrained by insufficient training data and conserv…
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…
GenNBV: Generalizable Next-Best-View Policy for Active 3D Reconstruction
Xiao Chen, Quanyi Li, Tai Wang +2
While recent advances in neural radiance field enable realistic digitization for large-scale scenes, the image-capturing process is still time-consuming and labor-intensive. Previo…
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…