cs.RO(2024-08-12)
📊 共 11 篇论文 | 🔗 2 篇有代码
🎯 兴趣领域导航
支柱一:机器人控制 (Robot Control) (5 🔗2)
支柱二:RL算法与架构 (RL & Architecture) (3)
支柱九:具身大模型 (Embodied Foundation Models) (3)
🔬 支柱一:机器人控制 (Robot Control) (5 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | TacSL: A Library for Visuotactile Sensor Simulation and Learning | TacSL:用于视觉触觉传感器仿真与学习的库,加速触觉策略学习。 | manipulation sim-to-real reinforcement learning | ✅ | |
| 2 | UniT: Data Efficient Tactile Representation with Generalization to Unseen Objects | UniT:一种数据高效的触觉表征学习方法,可泛化到未知物体 | manipulation policy learning representation learning | ✅ | |
| 3 | Developing Smart MAVs for Autonomous Inspection in GPS-denied Constructions | 提出一种用于GPS拒止环境自主巡检的智能MAV框架,实现高精度三维重建。 | motion planning 3D gaussian splatting gaussian splatting | ||
| 4 | EyeSight Hand: Design of a Fully-Actuated Dexterous Robot Hand with Integrated Vision-Based Tactile Sensors and Compliant Actuation | EyeSight Hand:集成视觉触觉传感器和柔顺驱动的灵巧机器人手 | humanoid manipulation dexterous manipulation | ||
| 5 | Motion Planning for Minimally Actuated Serial Robots | 针对最小驱动串联机器人,提出基于数据驱动逆运动学的MASR-RRT*运动规划算法。 | motion planning |
🔬 支柱二:RL算法与架构 (RL & Architecture) (3 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 6 | Retrieval-Augmented Hierarchical in-Context Reinforcement Learning and Hindsight Modular Reflections for Task Planning with LLMs | 提出RAHL框架,结合检索增强和分层强化学习,提升LLM在任务规划中的决策能力。 | reinforcement learning HMR large language model | ||
| 7 | Body Transformer: Leveraging Robot Embodiment for Policy Learning | 提出Body Transformer,利用机器人结构信息提升策略学习性能 | reinforcement learning policy learning | ||
| 8 | Stable-BC: Controlling Covariate Shift with Stable Behavior Cloning | Stable-BC:通过稳定行为克隆控制协变量偏移,提升模仿学习鲁棒性 | imitation learning behavior cloning |
🔬 支柱九:具身大模型 (Embodied Foundation Models) (3 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 9 | Generative Design of Multimodal Soft Pneumatic Actuators | 提出基于高斯混合模型的软气动执行器生成设计方法,实现多模态驱动。 | multimodal | ||
| 10 | Space-LLaVA: a Vision-Language Model Adapted to Extraterrestrial Applications | Space-LLaVA:针对地外应用场景的视觉-语言模型 | large language model foundation model instruction following | ||
| 11 | Text2Interaction: Establishing Safe and Preferable Human-Robot Interaction | Text2Interaction:利用大语言模型实现安全且符合用户偏好的人机交互 | large language model |