cs.RO(2024-10-30)

📊 共 14 篇论文 | 🔗 2 篇有代码

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支柱一:机器人控制 (Robot Control) (11 🔗1) 支柱二:RL算法与架构 (RL & Architecture) (2 🔗1) 支柱七:动作重定向 (Motion Retargeting) (1)

🔬 支柱一:机器人控制 (Robot Control) (11 篇)

#题目一句话要点标签🔗
1 An Efficient Representation of Whole-body Model Predictive Control for Online Compliant Dual-arm Mobile Manipulation 提出一种高效的全身模型预测控制方法,用于在线柔顺双臂移动操作 manipulation mobile manipulation dual-arm
2 EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning EMOTION:利用上下文学习为人形机器人生成富有表现力的运动序列 humanoid humanoid robot large language model
3 DisCo: Distributed Contact-Rich Trajectory Optimization for Forceful Multi-Robot Collaboration DisCo:用于强力多机器人协作的分布式接触轨迹优化算法 locomotion manipulation trajectory optimization
4 SoftCTRL: Soft conservative KL-control of Transformer Reinforcement Learning for Autonomous Driving 提出SoftCTRL,通过软保守KL控制Transformer强化学习,提升自动驾驶鲁棒性。 motion planning reinforcement learning imitation learning
5 EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents 提出EMOS框架,利用LLM智能体实现异构多机器人系统的具身感知协作。 manipulation HMR large language model
6 Human-inspired Grasping Strategies of Fresh Fruits and Vegetables Applied to Robotic Manipulation 提出一种受人类启发的抓取策略,用于机器人操作新鲜果蔬 manipulation
7 Non-contact Dexterous Micromanipulation with Multiple Optoelectronic Robots 提出基于光电效应的非接触式微操纵方法,实现复杂环境下微小物体的精准操控。 manipulation
8 Advancing Manipulation Capabilities of a UAV Featuring Dynamic Center-of-Mass Displacement 提出基于动态质心位移的无人机操作方法,提升力生成能力并扩展工具应用 manipulation
9 Learning for Deformable Linear Object Insertion Leveraging Flexibility Estimation from Visual Cues 提出基于视觉线索的柔性物体形变估计与强化学习策略,用于可变形线性物体插入任务 manipulation reinforcement learning policy learning
10 DexGraspNet 2.0: Learning Generative Dexterous Grasping in Large-scale Synthetic Cluttered Scenes DexGraspNet 2.0:提出基于扩散模型的生成式灵巧抓取方法,解决复杂场景下的抓取问题 dexterous hand sim-to-real
11 Design and Motion Analysis of a Reconfigurable Pendulum-Based Rolling Disk Robot with Magnetic Coupling 设计了一种基于磁耦合的可重构摆式滚动圆盘机器人,并分析了其运动特性 manipulation

🔬 支柱二:RL算法与架构 (RL & Architecture) (2 篇)

#题目一句话要点标签🔗
12 Keypoint Abstraction using Large Models for Object-Relative Imitation Learning KALM:利用大模型自动提取关键点,实现物体相对模仿学习 imitation learning
13 Multi-Task Interactive Robot Fleet Learning with Visual World Models 提出Sirius-Fleet框架,利用视觉世界模型提升多任务机器人集群在复杂环境中的泛化能力。 world model

🔬 支柱七:动作重定向 (Motion Retargeting) (1 篇)

#题目一句话要点标签🔗
14 Bridging the Human to Robot Dexterity Gap through Object-Oriented Rewards 提出HuDOR,通过面向对象的奖励函数弥合人手与机器人灵巧操作的差距 human-to-robot

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