3 citations · 3 across the 5 of their papers we have counts for
5 papers
Act, Sense, Act: Learning Active Perception from Large-Scale Egocentric Human Data
Jialiang Li, Yi Qiao, Yunhan Guo +2
Achieving generalizable manipulation in unconstrained environments requires the robot to proactively resolve information uncertainty, i.e., the capability of active perception. How…
Extendable Planning via Multiscale Diffusion
Chang Chen, Hany Hamed, Doojin Baek +4
Long-horizon planning is crucial in complex environments, but diffusion-based planners like Diffuser are limited by the trajectory lengths observed during training. This creates a…
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Chang Chen, Junyeob Baek, Fei Deng +3
Despite the recent advancements in offline RL, no unified algorithm could achieve superior performance across a broad range of tasks. Offline \textit{value function learning}, in p…
SCALE: Self-Correcting Visual Navigation for Mobile Robots via Anti-Novelty Estimation
Chang Chen, Yuecheng Liu, Yuzheng Zhuang +3
Although visual navigation has been extensively studied using deep reinforcement learning, online learning for real-world robots remains a challenging task. Recent work directly le…
Simple Hierarchical Planning with Diffusion
Chang Chen, Fei Deng, Kenji Kawaguchi +2
Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in general…