| 1 |
GS-Playground: A High-Throughput Photorealistic Simulator for Vision-Informed Robot Learning |
GS-Playground:高通量逼真模拟器加速视觉机器人学习 |
locomotion manipulation sim-to-real |
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| 2 |
ANCHOR: A Physically Grounded Closed-Loop Framework for Robust Home-Service Mobile Manipulation |
ANCHOR:面向家庭服务机器人,提出物理 grounding 的闭环框架,提升操作鲁棒性。 |
manipulation mobile manipulation semantic map |
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| 3 |
Privileged Foresight Distillation: Zero-Cost Future Correction for World Action Models |
提出特权前瞻蒸馏(PFD),用于提升世界行为模型的动作预测能力。 |
manipulation world action model world action models |
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| 4 |
KinDER: A Physical Reasoning Benchmark for Robot Learning and Planning |
KinDER:用于机器人学习与规划的物理推理基准测试 |
manipulation sim-to-real motion planning |
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| 5 |
Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance |
利用触觉和近邻觉信息,提升人型机器人避障能力 |
humanoid reinforcement learning egocentric |
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| 6 |
HANDFUL: Sequential Grasp-Conditioned Dexterous Manipulation with Resource Awareness |
HANDFUL:资源感知的序列抓取条件灵巧操作学习框架 |
manipulation dexterous manipulation policy learning |
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| 7 |
Sensitivity-Based Tube NMPC for Cooperative Aerial Structures Under Parametric Uncertainty |
提出基于灵敏度的Tube NMPC方法,解决参数不确定性下合作式空中链的鲁棒控制问题 |
model predictive control |
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