cs.RO（2025-10-25）

📊 共 9 篇论文 | 🔗 3 篇有代码

🎯 兴趣领域导航

支柱一：机器人控制 (Robot Control) (4 🔗2) 支柱二：RL算法与架构 (RL & Architecture) (3) 支柱八：物理动画 (Physics-based Animation) (1) 支柱三：空间感知与语义 (Perception & Semantics) (1 🔗1)

🔬 支柱一：机器人控制 (Robot Control) (4 篇)

#	题目	一句话要点	标签	🔗	⭐
1	ACG: Action Coherence Guidance for Flow-based VLA models	提出动作连贯性引导（ACG）方法，提升基于流的VLA模型在机器人操作任务中的性能。	manipulation imitation learning flow matching	✅
2	EasyUUV: An LLM-Enhanced Universal and Lightweight Sim-to-Real Reinforcement Learning Framework for UUV Attitude Control	EasyUUV：基于LLM的通用轻量级水下机器人姿态控制Sim-to-Real强化学习框架	sim-to-real reinforcement learning large language model	✅
3	Toward Humanoid Brain-Body Co-design: Joint Optimization of Control and Morphology for Fall Recovery	提出RoboCraft框架，联合优化人形机器人控制与形态，提升跌倒恢复能力。	humanoid humanoid robot locomotion
4	RaycastGrasp: Eye-Gaze Interaction with Wearable Devices for Robotic Manipulation	RaycastGrasp：基于眼动追踪和可穿戴设备的机器人操作交互	manipulation egocentric

🔬 支柱二：RL算法与架构 (RL & Architecture) (3 篇)

#	题目	一句话要点	标签	🔗	⭐
5	BLIP-FusePPO: A Vision-Language Deep Reinforcement Learning Framework for Lane Keeping in Autonomous Vehicles	提出BLIP-FusePPO，用于自动驾驶车辆车道保持的多模态强化学习框架	reinforcement learning deep reinforcement learning policy learning
6	Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site Assessment	NeuroSymLand：结合神经符号推理，实现可解释的安全无人机着陆点评估	world model large language model
7	A Novel Multi-Timescale Stability-Preserving Hierarchical Reinforcement Learning Controller Framework for Adaptive Control in High-Dimensional Dynamical Systems	提出多时间尺度Lyapunov约束分层强化学习框架，解决高维动态系统自适应控制问题。	reinforcement learning

🔬 支柱八：物理动画 (Physics-based Animation) (1 篇)

#	题目	一句话要点	标签	🔗	⭐
8	Estimating Continuum Robot Shape under External Loading using Spatiotemporal Neural Networks	提出时空神经网络，融合多模态信息，精确估计受载连续体机器人的形状。	spatiotemporal

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

#	题目	一句话要点	标签	🔗	⭐
9	Breaking the Static Assumption: A Dynamic-Aware LIO Framework Via Spatio-Temporal Normal Analysis	提出一种动态感知LIO框架，通过时空法线分析解决动态环境下的定位问题	LIO	✅

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