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VLA-RFT: Vision-Language-Action Reinforcement Fine-tuning with Verified Rewards in World Simulators |
VLA-RFT:基于世界模型和验证奖励的视觉-语言-动作强化微调 |
sim-to-real reinforcement learning imitation learning |
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| 2 |
Conflict-Based Search as a Protocol: A Multi-Agent Motion Planning Protocol for Heterogeneous Agents, Solvers, and Independent Tasks |
提出基于冲突搜索协议的多智能体异构运动规划方法 |
motion planning reinforcement learning |
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| 3 |
Hybrid Training for Vision-Language-Action Models |
提出混合训练HyT框架,加速视觉-语言-动作模型推理,兼顾性能与效率。 |
manipulation vision-language-action large language model |
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| 4 |
HAMLET: Switch your Vision-Language-Action Model into a History-Aware Policy |
HAMLET:将视觉-语言-动作模型转化为历史感知策略,提升机器人操作性能 |
manipulation contrastive learning vision-language-action |
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| 5 |
Shared Object Manipulation with a Team of Collaborative Quadrupeds |
提出基于腿式机器人团队的共享物体操作方法,解决复杂环境下的物体搬运问题 |
quadruped manipulation loco-manipulation |
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| 6 |
AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation |
AFFORD2ACT:提出基于可供性的自动关键点选择方法,用于通用且轻量级的机器人操作 |
manipulation policy learning affordance |
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| 7 |
From Human Hands to Robot Arms: Manipulation Skills Transfer via Trajectory Alignment |
Traj2Action:通过轨迹对齐实现人手操作技能向机器人手臂的迁移 |
manipulation policy learning human-to-robot |
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| 8 |
Safe Motion Planning and Control Using Predictive and Adaptive Barrier Methods for Autonomous Surface Vessels |
提出基于预测和自适应控制屏障函数的自主水面艇安全运动规划方法 |
MPC model predictive control motion planning |
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| 9 |
RTFF: Random-to-Target Fabric Flattening Policy using Dual-Arm Manipulator |
提出RTFF策略,利用双臂机器人实现任意褶皱织物到目标平整状态的对齐 |
manipulation dual-arm imitation learning |
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| 10 |
Differentiable Skill Optimisation for Powder Manipulation in Laboratory Automation |
提出基于可微技能优化的粉末操作方法,用于实验室自动化。 |
manipulation reinforcement learning |
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| 11 |
Prometheus: Universal, Open-Source Mocap-Based Teleoperation System with Force Feedback for Dataset Collection in Robot Learning |
Prometheus:基于动捕和力反馈的通用开源遥操作系统,用于机器人学习数据集采集 |
teleoperation imitation learning |
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| 12 |
GRITS: A Spillage-Aware Guided Diffusion Policy for Robot Food Scooping Tasks |
GRITS:一种用于机器人食物舀取任务的防溢出引导扩散策略 |
manipulation diffusion policy |
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| 13 |
CroSTAta: Cross-State Transition Attention Transformer for Robotic Manipulation |
提出Cross-State Transition Attention Transformer以解决机器人操作中的执行变异问题 |
manipulation |
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| 14 |
How Well do Diffusion Policies Learn Kinematic Constraint Manifolds? |
研究扩散策略学习运动学约束流形的能力,揭示数据集质量和大小的影响。 |
bi-manual imitation learning |
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