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cs.RO2026

Schrödinger's Navigator: Imagining an Ensemble of Futures for Zero-Shot Object Navigation

Yu He, Da Huang, Zhenyang Liu +5

Zero-shot object navigation (ZSON) requires robots to find target objects in unseen environments without task-specific fine-tuning or pre-built maps, a key capability for general-p…

cs.RO2026

VADF: Vision-Adaptive Diffusion Policy Framework for Efficient Robotic Manipulation

Xinglei Yu, Zhenyang Liu, Shufeng Nan +2

Diffusion policies are becoming mainstream in robotic manipulation but suffer from hard negative class imbalance due to uniform sampling and lack of sample difficulty awareness, le…

cs.RO2026

ActiveVLA: Injecting Active Perception into Vision-Language-Action Models for Precise 3D Robotic Manipulation

Zhenyang Liu, Yongchong Gu, Yikai Wang +2

Recent advances in robot manipulation have leveraged pre-trained vision-language models (VLMs) and explored integrating 3D spatial signals into these models for effective action pr…

cs.RO2025

TriVLA: A Triple-System-Based Unified Vision-Language-Action Model with Episodic World Modeling for General Robot Control

Zhenyang Liu, Yongchong Gu, Sixiao Zheng +3

Recent advances in vision-language models (VLMs) have enabled robots to follow open-ended instructions and demonstrate impressive commonsense reasoning. However, current vision-lan…

cs.RO2025

Spatial-Temporal Aware Visuomotor Diffusion Policy Learning

Zhenyang Liu, Yikai Wang, Kuanning Wang +3

Visual imitation learning is effective for robots to learn versatile tasks. However, many existing methods rely on behavior cloning with supervised historical trajectories, limitin…