cs.RO（2024-09-21）

📊 共 10 篇论文 | 🔗 2 篇有代码

🎯 兴趣领域导航

支柱一：机器人控制 (Robot Control) (4 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (3 🔗1) 支柱三：空间感知与语义 (Perception & Semantics) (2) 支柱九：具身大模型 (Embodied Foundation Models) (1)

🔬 支柱一：机器人控制 (Robot Control) (4 篇)

#	题目	一句话要点	标签	🔗	⭐
1	KALIE: Fine-Tuning Vision-Language Models for Open-World Manipulation without Robot Data	KALIE：无需机器人数据，微调视觉-语言模型用于开放世界操作	manipulation affordance affordance-aware
2	ScissorBot: Learning Generalizable Scissor Skill for Paper Cutting via Simulation, Imitation, and Sim2Real	ScissorBot：通过仿真、模仿学习和Sim2Real实现通用剪纸技能	sim-to-real sim2real imitation learning
3	IMOST: Incremental Memory Mechanism with Online Self-Supervision for Continual Traversability Learning	提出IMOST框架，解决连续可通行性学习中的知识遗忘与标注稀疏问题	quadruped traversability	✅
4	Aerial Grasping with Soft Aerial Vehicle Using Disturbance Observer-Based Model Predictive Control	提出基于扰动观测器的模型预测控制软体无人机空中抓取方案	model predictive control

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

#	题目	一句话要点	标签	🔗	⭐
5	Stabilization of vertical motion of a vehicle on bumpy terrain using deep reinforcement learning	提出基于深度强化学习的速度控制方法，用于稳定崎岖地形车辆的垂直运动	reinforcement learning deep reinforcement learning
6	R-AIF: Solving Sparse-Reward Robotic Tasks from Pixels with Active Inference and World Models	提出R-AIF，结合主动推理与世界模型，解决像素输入下的稀疏奖励机器人任务。	preference learning world model	✅
7	VLM-Vac: Enhancing Smart Vacuums through VLM Knowledge Distillation and Language-Guided Experience Replay	VLM-Vac：通过VLM知识蒸馏和语言引导经验回放增强智能吸尘器自主性	distillation

🔬 支柱三：空间感知与语义 (Perception & Semantics) (2 篇)

#	题目	一句话要点	标签	🔗	⭐
8	GND: Global Navigation Dataset with Multi-Modal Perception and Multi-Category Traversability in Outdoor Campus Environments	提出GND：一个多模态、多类别可通行性的大规模室外校园导航数据集	traversability
9	Relevance-driven Decision Making for Safer and More Efficient Human Robot Collaboration	提出基于相关性的决策框架，提升人机协作的安全性和效率	scene understanding motion generation

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

#	题目	一句话要点	标签	🔗	⭐
10	Integrated Decision Making and Trajectory Planning for Autonomous Driving Under Multimodal Uncertainties: A Bayesian Game Approach	提出基于贝叶斯博弈的决策与轨迹规划框架，解决自动驾驶中多模态不确定性下的交互问题。	multimodal

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