cs.RO（2025-06-30）

📊 共 12 篇论文 | 🔗 2 篇有代码

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支柱一：机器人控制 (Robot Control) (10 🔗2) 支柱二：RL算法与架构 (RL & Architecture) (2)

🔬 支柱一：机器人控制 (Robot Control) (10 篇)

#题目一句话要点标签🔗⭐
1 Goal-VLA: Image-Generative VLMs as Object-Centric World Models Empowering Zero-shot Robot Manipulation 提出Goal-VLA以解决机器人操作中的泛化问题 manipulation world model vision-language-action ✅
2 PAC Bench: Do Foundation Models Understand Prerequisites for Executing Manipulation Policies? 提出PAC Bench以评估基础模型对操作策略执行前提的理解能力 humanoid manipulation affordance
3 Mechanical Intelligence-Aware Curriculum Reinforcement Learning for Humanoids with Parallel Actuation 提出机械智能感知的课程强化学习以优化类人机器人运动控制 humanoid humanoid robot locomotion ✅
4 Towards Universal Shared Control in Teleoperation Without Haptic Feedback 提出多目标优化方法以解决无触觉反馈的遥操作问题 teleoperation shared control
5 When Digital Twins Meet Large Language Models: Realistic, Interactive, and Editable Simulation for Autonomous Driving 提出统一框架以解决自主驾驶仿真中的多重挑战 real2sim large language model
6 Sim2Real Diffusion: Leveraging Foundation Vision Language Models for Adaptive Automated Driving 提出统一框架以解决自动驾驶的sim2real转移问题 sim2real foundation model
7 Motion Tracking with Muscles: Predictive Control of a Parametric Musculoskeletal Canine Model 提出基于肌肉的运动追踪模型以解决犬类运动控制问题 locomotion motion tracking
8 Adapt Your Body: Mitigating Proprioception Shifts in Imitation Learning 提出领域适应框架以解决模仿学习中的本体感知偏移问题 manipulation imitation learning
9 A comprehensive control architecture for semi-autonomous dual-arm robots in agriculture settings 提出一种综合控制架构以解决农业环境中双臂机器人任务管理问题 dual-arm
10 Novel Design of 3D Printed Tumbling Microrobots for in vivo Targeted Drug Delivery 提出3D打印翻滚微型机器人以解决靶向药物递送问题 locomotion

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

#题目一句话要点标签🔗⭐
11 Control-Optimized Deep Reinforcement Learning for Artificially Intelligent Autonomous Systems 提出控制优化深度强化学习以解决执行不匹配问题 reinforcement learning deep reinforcement learning DRL
12 Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Driving 提出多时间尺度层次强化学习以解决自动驾驶行为与控制统一问题 reinforcement learning multimodal

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