| 1 |
PRISM: Personalized Robotic Dataset Generation via Image-based Scene and Motion Synthesis |
提出PRISM以解决个性化机器人数据集生成问题 |
manipulation teleoperation policy learning |
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| 2 |
DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation |
提出DSWAM以解决机器人操作中的任务分解问题 |
manipulation world model world models |
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| 3 |
Athena-WBC: Capability-Aligned Policy Experts for Long-Tail Humanoid Whole-Body Control |
提出Athena-WBC以解决长尾人形机器人全身控制问题 |
humanoid whole-body control motion tracking |
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| 4 |
KAM-WM: Kinematic Affordance Maps from Latent World Models for Robot Manipulation |
提出KAM-WM框架以解决机器人操作中的视觉先验问题 |
manipulation diffusion policy flow matching |
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| 5 |
CAC-VLA: Context-Gated Action Conditioning for Vision-Language-Action Models |
提出CAC-VLA以解决视觉-语言-动作模型的动作条件化问题 |
manipulation vision-language-action VLA |
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| 6 |
Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation |
提出零-shot方法以解决多指灵巧手的现实差距问题 |
manipulation dexterous hand dexterous manipulation |
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| 7 |
Simple-to-Complex Structured Demonstrations for Vision-Language-Action Learning |
提出简单到复杂的演示收集策略以提升VLA学习效率 |
manipulation dual-arm policy learning |
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| 8 |
Geometry-Aware Motion Latents for Learning Robust Manipulation Policies |
提出GeoMoLa以解决机器人操作中的运动模式学习问题 |
manipulation motion latent |
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| 9 |
Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models |
提出Deform360以解决可变形物体建模挑战 |
manipulation bi-manual world model |
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| 10 |
Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation |
提出Cortex框架以解决长时间操作中的规划与执行问题 |
manipulation vision-language-action VLA |
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| 11 |
SILO: Simulation-in-the-Loop Sim-to-Real Transfer for Multi-Stage Cable Routing |
提出SILO框架以解决多阶段电缆布线的仿真到现实转移问题 |
manipulation sim-to-real reinforcement learning |
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| 12 |
GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks |
提出GaP以解决变异自动化任务中的可靠性问题 |
motion planning task and motion planning TAMP |
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| 13 |
InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization |
提出InternVLA-A1.5以解决机器人操作中的语义与动态预测问题 |
manipulation world model world models |
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| 14 |
Aerial Manipulation: Contact, Medium Coupling, and the Geometry of Readiness |
提出介质感知的空中操控方法以解决传统操控不足问题 |
locomotion manipulation |
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| 15 |
HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors |
提出HUGS框架以解决多模式多尺度灵巧抓取问题 |
bi-manual |
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