cs.RO（2024-06-17）

📊 共 14 篇论文 | 🔗 3 篇有代码

🎯 兴趣领域导航

支柱一：机器人控制 (Robot Control) (10 🔗1) 支柱九：具身大模型 (Embodied Foundation Models) (2 🔗1) 支柱七：动作重定向 (Motion Retargeting) (1) 支柱二：RL算法与架构 (RL & Architecture) (1 🔗1)

🔬 支柱一：机器人控制 (Robot Control) (10 篇)

#题目一句话要点标签🔗⭐
1 Minimal Self in Humanoid Robot "Alter3" Driven by Large Language Model Alter3：基于大语言模型驱动的人形机器人，探索“最小自我” humanoid humanoid robot motion generation
2 AIC MLLM: Autonomous Interactive Correction MLLM for Robust Robotic Manipulation 提出AIC MLLM，利用交互经验纠正机器人操作中SE(3)位姿预测，提升操作鲁棒性 manipulation large language model multimodal
3 Embedded Hierarchical MPC for Autonomous Navigation 提出嵌入式分层MPC，提升四旋翼无人机在复杂环境中的自主导航性能。 MPC model predictive control
4 Imagination Policy: Using Generative Point Cloud Models for Learning Manipulation Policies 提出Imagination Policy，利用生成点云模型学习高精度操作策略 manipulation
5 FetchBench: A Simulation Benchmark for Robot Fetching 提出FetchBench：一个用于机器人抓取的模拟基准测试平台 manipulation motion planning imitation learning
6 Propagative Distance Optimization for Constrained Inverse Kinematics 提出PDO-IK算法，利用链式结构优化距离，高效解决约束逆运动学问题 humanoid humanoid robot
7 Fingertip Contact Force Direction Control using Tactile Feedback 提出一种基于触觉反馈的指尖接触力方向控制方法，用于灵巧手操作。 manipulation dexterous manipulation
8 Online Pareto-Optimal Decision-Making for Complex Tasks using Active Inference 提出基于主动推理的在线帕累托最优决策框架，用于复杂任务中的多目标优化。 manipulation reinforcement learning
9 A Brief Survey on Leveraging Large Scale Vision Models for Enhanced Robot Grasping 综述：利用大规模视觉模型增强机器人抓取性能 manipulation visual pre-training
10 Graspness Discovery in Clutters for Fast and Accurate Grasp Detection 提出 Graspness 用于杂乱场景下的快速精确抓取姿态检测 manipulation ✅

🔬 支柱九：具身大模型 (Embodied Foundation Models) (2 篇)

#题目一句话要点标签🔗⭐
11 Embodied Instruction Following in Unknown Environments 提出基于多模态大语言模型的具身智能指令跟随方法，解决未知环境下的复杂任务规划问题 large language model multimodal instruction following ✅
12 Enabling robots to follow abstract instructions and complete complex dynamic tasks 提出结合LLM、知识库与力觉/视觉反馈的机器人控制框架，解决复杂动态任务 large language model

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

#题目一句话要点标签🔗⭐
13 GRID-FAST: A Grid-based Intersection Detection for Fast Semantic Topometric Mapping 提出GRID-FAST以解决移动机器人快速语义拓扑映射问题 human-to-robot

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

#题目一句话要点标签🔗⭐
14 Online Context Learning for Socially Compliant Navigation 提出在线情境学习方法，提升机器人在复杂社交环境中的导航能力。 reinforcement learning deep reinforcement learning ✅

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