cs.RO（2024-11-29）

📊 共 8 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 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (2 🔗1) 支柱九：具身大模型 (Embodied Foundation Models) (1)

🔬 支柱一：机器人控制 (Robot Control) (5 篇)

#	题目	一句话要点	标签	🔗	⭐
1	CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation	CogACT：用于机器人操作中认知与行动协同的基础视觉-语言-动作模型	manipulation vision-language-action VLA
2	Improving generalization of robot locomotion policies via Sharpness-Aware Reinforcement Learning	提出基于锐度感知强化学习的机器人运动策略泛化方法	locomotion locomotion policy sim-to-real
3	RoboMatrix: A Skill-centric Hierarchical Framework for Scalable Robot Task Planning and Execution in Open-World	RoboMatrix：面向开放世界，基于技能分层框架实现可扩展机器人任务规划与执行	manipulation vision-language-action VLA	✅
4	Grasping and Rolling In-plane Manipulation Using Deployable Tape spring Appendages	GRIP-tape：利用可展开带簧结构实现平面抓取和滚动操作	manipulation bi-manual
5	The ATTUNE model for Artificial Trust Towards Human Operators	提出ATTUNE模型，用于量化人机交互中机器人对人类操作员的人工信任。	teleoperation

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

#	题目	一句话要点	标签	🔗	⭐
6	One-Shot Real-to-Sim via End-to-End Differentiable Simulation and Rendering	提出基于可微模拟与渲染的单样本Real-to-Sim方法，用于机器人环境建模。	world model differentiable simulation	✅
7	SANGO: Socially Aware Navigation through Grouped Obstacles	SANGO：通过分组障碍物的社交感知导航方法	reinforcement learning deep reinforcement learning PPO

🔬 支柱九：具身大模型 (Embodied Foundation Models) (1 篇)

#	题目	一句话要点	标签	🔗	⭐
8	Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model	AutoScenario：基于多模态LLM生成自动驾驶逼真极端场景，提升系统安全性。	large language model multimodal

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