cs.RO(2025-05-04)

📊 共 10 篇论文 | 🔗 1 篇有代码

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支柱一:机器人控制 (Robot Control) (7 🔗1) 支柱九:具身大模型 (Embodied Foundation Models) (1) 支柱二:RL算法与架构 (RL & Architecture) (1) 支柱三:空间感知与语义 (Perception & Semantics) (1)

🔬 支柱一:机器人控制 (Robot Control) (7 篇)

#题目一句话要点标签🔗
1 Interleave-VLA: Enhancing Robot Manipulation with Interleaved Image-Text Instructions Interleave-VLA:利用交错图像-文本指令增强机器人操作能力 manipulation vision-language-action VLA
2 KineDex: Learning Tactile-Informed Visuomotor Policies via Kinesthetic Teaching for Dexterous Manipulation KineDex:通过动觉示教学习触觉感知的灵巧操作策略 manipulation dexterous hand dexterous manipulation
3 CrayonRobo: Object-Centric Prompt-Driven Vision-Language-Action Model for Robotic Manipulation CrayonRobo:面向机器人操作的、以物体为中心的提示驱动视觉-语言-动作模型 manipulation vision-language-action
4 Dexterous Contact-Rich Manipulation via the Contact Trust Region 提出接触信任域(CTR)方法,高效解决灵巧操作中的接触动力学建模与规划问题 manipulation in-hand manipulation bi-manual
5 Prompt-responsive Object Retrieval with Memory-augmented Student-Teacher Learning 提出一种基于记忆增强学生-教师学习的提示响应式物体抓取方法 manipulation dexterous manipulation reinforcement learning
6 Bridging Model Predictive Control and Deep Learning for Scalable Reachability Analysis 提出一种结合模型预测控制与深度学习的可扩展可达性分析方法 MPC model predictive control
7 Robust Localization, Mapping, and Navigation for Quadruped Robots 针对低成本四足机器人,提出稳健的定位、建图与导航系统 quadruped reinforcement learning

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

#题目一句话要点标签🔗
8 DriveAgent: Multi-Agent Structured Reasoning with LLM and Multimodal Sensor Fusion for Autonomous Driving DriveAgent:融合LLM与多模态传感器,实现自主驾驶中的多智能体结构化推理 large language model multimodal TAMP

🔬 支柱二:RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗
9 A Goal-Oriented Reinforcement Learning-Based Path Planning Algorithm for Modular Self-Reconfigurable Satellites 提出基于目标导向强化学习的模块化自重构卫星路径规划算法 reinforcement learning

🔬 支柱三:空间感知与语义 (Perception & Semantics) (1 篇)

#题目一句话要点标签🔗
10 SafeNav: Safe Path Navigation using Landmark Based Localization in a GPS-denied Environment 提出基于地标定位的LanBLoc-BMM导航方法,解决GPS拒止环境下的安全路径规划问题 visual odometry

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