9 accepted papers
Extrinsic dexterity leverages environmental contact to overcome the limitations of prehensile manipulation. However, achieving such dexterity in cluttered scenes remains challenging and underexplored, as it requires selectively exploiting contact among multiple interacting objects with inherently co…
Vision-Language-Action (VLA) models benefit from Chain-of-Thought (CoT) reasoning, but existing approaches incur high inference overhead and rely on discrete reasoning representations that mismatch continuous perception and control. We propose Latent Reasoning VLA (LaRA-VLA), a unified VLA framework…
Multi-objective discrete optimization problems, such as molecular design, pose significant challenges due to their vast and unstructured combinatorial spaces. Traditional evolutionary algorithms often get trapped in local optima, while expert knowledge can provide crucial guidance for accelerating c…
While Vision-Language-Action (VLA) models excel in generalist manipulation, they often lack fine-grained spatial awareness and struggle with viewpoint generalization. This limitation largely stems from the reliance on pretrained RGB encoders, which lack explicit geometric cues and prioritize semanti…
Video Corpus Moment Retrieval (VCMR) is a challenging task that aims to localize query-specified moments from a collection of untrimmed videos. The recent state-of-the-art method, JSG, tries to tackle this task using only video-level annotations in a weakly-supervised setting. However, the late fusi…
Partially Relevant Video Retrieval (PRVR) is a practical yet challenging task that involves retrieving videos based on queries relevant to only specific segments. While existing works follow the paradigm of developing models to process unimodal features, powerful pretrained vision-language models li
Video corpus moment retrieval (VCMR) is a challenging task aimed at localizing specific segments from untrimmed videos within a vast video collection. It has long been addressed using end-to-end supervised or weakly-supervised methods, which often lack explainability and rely on laborious annotation…
We develop two cooperative robots for power transmission lines (PTLs) inspection - a light climbing robot (CBR) which can stably move on the overhead ground wire (OGW) for sensor data collection and an unmanned aerial vehicle (UAV) with a grabbing mechanism, which can automatically put the CBR on th…
This paper proposes a unique and robust UAV autonomous navigation approach along one side of overhead transmission lines for inspection. To this end, we establish a perspective model and develop a novel Pan/Tilt monocular-based navigation scheme. Simultaneously, the following three key issues are ad…