GPT-6 Astra exhibits a remarkable ability to generate numerical robot actions, extending its role beyond high-level planning. To assess Astra's capabilities as general-purpose embodied policies, we conduct comprehensive evaluations across six domains, examining direct control, cooperation with learned policies, and fee...
Galbot Team Xuchuan Chen, Xiao-Qi Cheng, Yu Deng et al.· 0 citations
Humanoid robots can step over, squeeze past, and duck under obstacles, but learning to select and coordinate these behaviors from onboard perception remains challenging. Many existing approaches rely on task-specific reinforcement-learning objectives or curated motion libraries, making broad behavioral coverage costly....
Yuxuan Ma, Zi-Cheng Zeng, Chun-Li Peng et al.· 1 citation
Enabling humanoid robots to respond to human speech with synchronized and semantically meaningful gestures is fundamental to natural human-robot interaction. However, this task faces three critical barriers: the scarcity of semantically rich datasets, the"modality eclipse"where models ignore audio cues in favor of kine...
Zi-Fan Wang, Ziang Ren, Pengteng Shi et al.· 4 citations
This work introduces HumanTracker, a preference-aligned metric trained on 12K motion pairs containing 24K motions that better predicts human preferences and reveals contact and stability failures that kinematic metrics often miss.
Dai-En Liu, Ze-Kun Qi, Jia-Yu Zeng et al.· 0 citations
This work revisits the scaling recipe for BFMs and demonstrates that substantial performance gains can be achieved through the coordination of three core components: the learning paradigm of motion tracking that reformulates diverse humanoid control problems as the reproduction of integrated whole-body behaviors in the...
