cs.RO(2024-03-13)

📊 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) (12 🔗2) 支柱三:空间感知与语义 (Perception & Semantics) (1 🔗1) 支柱九:具身大模型 (Embodied Foundation Models) (1)

🔬 支柱一:机器人控制 (Robot Control) (12 篇)

#题目一句话要点标签🔗
1 ManiGaussian: Dynamic Gaussian Splatting for Multi-task Robotic Manipulation 提出ManiGaussian以解决多任务机器人操控中的场景动态问题 manipulation world model world models
2 Language-Grounded Dynamic Scene Graphs for Interactive Object Search with Mobile Manipulation 提出MoMa-LLM以解决移动操控机器人在未知环境中的任务执行问题 manipulation mobile manipulation open-vocabulary
3 CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models 提出CoPa框架以解决机器人操作中的空间约束问题 manipulation motion planning foundation model
4 NaturalVLM: Leveraging Fine-grained Natural Language for Affordance-Guided Visual Manipulation 提出NaturalVLM以解决机器人复杂操作中的语言理解问题 manipulation affordance
5 Synchronized Dual-arm Rearrangement via Cooperative mTSP 提出基于合作mTSP的同步双臂重排方法以解决可扩展性问题 dual-arm reinforcement learning spatial relationship
6 DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation 提出DIFFTACTILE以解决机器人操作中的触觉反馈不足问题 manipulation sim-to-real
7 Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks 提出在线多接触反馈模型预测控制以解决交互式机器人任务 MPC model predictive control
8 SpaceOctopus: An Octopus-inspired Motion Planning Framework for Multi-arm Space Robot 提出基于章鱼启发的运动规划框架以解决多臂空间机器人问题 motion planning reinforcement learning
9 MorphoGear: An UAV with Multi-Limb Morphogenetic Gear for Rough-Terrain Locomotion 提出MorphoGear以解决复杂环境下的多功能移动问题 locomotion
10 Collision-Free Platooning of Mobile Robots through a Set-Theoretic Predictive Control Approach 提出基于集合理论的预测控制方法以实现移动机器人无碰撞编队 model predictive control
11 Perceive With Confidence: Statistical Safety Assurances for Navigation with Learning-Based Perception 提出基于学习感知的导航安全保障方法 quadruped
12 Prosody for Intuitive Robotic Interface Design: It's Not What You Said, It's How You Said It 利用韵律设计直观的人机交互界面以提升机器人导航能力 quadruped

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

#题目一句话要点标签🔗
13 Empowering Robot Path Planning with Large Language Models: osmAG Map Topology & Hierarchy Comprehension with LLMs 利用大语言模型提升机器人路径规划的地图理解能力 semantic map large language model

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

#题目一句话要点标签🔗
14 Scaling Instructable Agents Across Many Simulated Worlds 提出可扩展的指令代理以解决多种模拟环境中的任务执行问题 embodied AI

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