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From the 1 of 43 linked papers with an AI index.

activity
20242026
most citedOpen-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP

1 citations · 1 across the 4 of their papers we have counts for

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43 papers

cs.RO2026

X-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching

Tianyu Yang, Yiming Zeng, Wenzhe Cai +5

The paper introduces X-NavDP, a diffusion-based visual navigation policy that is fine‑tuned with a novel Group Q-score Reweighted Matching (GQRM) reinforcement learning framework t…

cs.RO2026

ReSim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation

Xiaoshen Han, Junqiu Yu, Minghuan Liu +6

Real-world data collection for robotics is costly and resource-intensive, requiring skilled operators and expensive hardware. Simulations offer a scalable alternative but often fai…

cs.RO2026

StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling

Meng Wei, Chenyang Wan, Xiqian Yu +9

Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low latency grounded in language instruct…

cs.RO20261 cited

Open-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP

Meng Wei, Chenyang Wan, Tai Wang +6

Object-oriented embodied navigation tasks require agents to locate specific objects, either defined by category or images, in unseen environments. While recent methods have made pr…

cs.RO2026

ReactiveBFM: Reactive Closed-Loop Motion Planning Towards Universal Humanoid Whole-Body Control

Xiao Chen, Weishuai Zeng, Xiaojie Niu +12

While current Behavior Foundation Models (BFMs) provide robust control priors for humanoids, they only execute pre-defined reference motions. As a result, they are vulnerable to en…

cs.RO2026

Demystifying Action Space Design for Robotic Manipulation Policies

Yuchun Feng, Jinliang Zheng, Zhihao Wang +5

The specification of the action space plays a pivotal role in imitation-based robotic manipulation policy learning, fundamentally shaping the optimization landscape of policy learn…