| 1 |
A General One-Shot Multimodal Active Perception Framework for Robotic Manipulation: Learning to Predict Optimal Viewpoint |
提出一种通用单次多模态主动感知框架,用于机器人操作中的最优视角预测 |
manipulation sim-to-real domain randomization |
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| 2 |
DroneVLA: VLA based Aerial Manipulation |
提出基于VLA的无人机空中操作系统,实现自然语言指令控制下的物体抓取与递送。 |
manipulation vision-language-action VLA |
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| 3 |
Communication-Free Collective Navigation for a Swarm of UAVs via LiDAR-Based Deep Reinforcement Learning |
提出基于激光雷达和深度强化学习的无人机集群无通信自主导航方法 |
sim-to-real reinforcement learning deep reinforcement learning |
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| 4 |
RoboBrain 2.5: Depth in Sight, Time in Mind |
RoboBrain 2.5:通过时空监督学习,提升具身智能体的3D空间推理和时间建模能力。 |
manipulation spatiotemporal embodied AI |
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| 5 |
TwinBrainVLA: Unleashing the Potential of Generalist VLMs for Embodied Tasks via Asymmetric Mixture-of-Transformers |
TwinBrainVLA:通过非对称混合Transformer释放通用VLM在具身任务中的潜力 |
manipulation flow matching vision-language-action |
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| 6 |
Active Cross-Modal Visuo-Tactile Perception of Deformable Linear Objects |
提出基于主动跨模态视觉-触觉融合的柔性线性物体三维重建方法 |
manipulation foundation model |
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| 7 |
SandWorm: Event-based Visuotactile Perception with Active Vibration for Screw-Actuated Robot in Granular Media |
SandWorm:基于事件相机的振动触觉感知系统,用于颗粒介质中螺杆驱动机器人 |
locomotion |
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| 8 |
Group-Invariant Unsupervised Skill Discovery: Symmetry-aware Skill Representations for Generalizable Behavior |
提出群不变技能发现框架,提升对称环境中无监督技能学习的泛化性与效率。 |
locomotion |
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