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Teach and Grow: An Agent-Centered Architecture for General Robot Learning
Chang Nie, Zhe Liu, Hesheng Wang
Vision-language-action (VLA) and world-action models typically absorb unfamiliar manipulation tasks through additional robot data collection and policy optimization. This recurring…
Towards the Vision-Sound-Language-Action Paradigm: The HEAR Framework for Sound-Centric Manipulation
Chang Nie, Tianchen Deng, Guangming Wang +2
While recent Vision-Language-Action (VLA) models have begun to incorporate audio, they typically treat sound as static pre-execution prompts or focus exclusively on human speech. T…
PILOT: A Perceptive Integrated Low-level Controller for Loco-manipulation over Unstructured Scenes
Xinru Cui, Linxi Feng, Yixuan Zhou +3
Humanoid robots hold great potential for diverse interactions and daily service tasks within human-centered environments, necessitating controllers that seamlessly integrate precis…
Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation
Yiyuan Pan, Yunzhe Xu, Zhe Liu +1
Visual navigation is a fundamental problem in embodied AI, yet practical deployments demand long-horizon planning capabilities to address multi-objective tasks. A major bottleneck…
Foresee and Act Ahead: Task Prediction and Pre-Scheduling Enabled Efficient Robotic Warehousing
B. Cao, Z. Liu, X. Han +3
In warehousing systems, to enhance logistical efficiency amid surging demand volumes, much focus is placed on how to reasonably allocate tasks to robots. However, the robots labor…
Enhancing Exploratory Capability of Visual Navigation Using Uncertainty of Implicit Scene Representation
Yichen Wang, Qiming Liu, Zhe Liu +1
In the context of visual navigation in unknown scenes, both "exploration" and "exploitation" are equally crucial. Robots must first establish environmental cognition through explor…