cs.RO(2025-07-08)

📊 共 13 篇论文 | 🔗 1 篇有代码

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支柱一:机器人控制 (Robot Control) (9) 支柱三:空间感知与语义 (Perception & Semantics) (2 🔗1) 支柱九:具身大模型 (Embodied Foundation Models) (1) 支柱二:RL算法与架构 (RL & Architecture) (1)

🔬 支柱一:机器人控制 (Robot Control) (9 篇)

#题目一句话要点标签🔗
1 Integrating Diffusion-based Multi-task Learning with Online Reinforcement Learning for Robust Quadruped Robot Control DMLoco:融合扩散模型多任务学习与在线强化学习的鲁棒四足机器人控制框架 quadruped legged robot legged locomotion
2 Evaluating Robots Like Human Infants: A Case Study of Learned Bipedal Locomotion 借鉴婴儿行为评估方法,研究强化学习双足机器人运动控制器的训练策略。 bipedal biped locomotion
3 Is Diversity All You Need for Scalable Robotic Manipulation? 揭示数据多样性对可扩展机器人操作的影响,并提出速度解偏方法。 manipulation policy learning cross-embodiment
4 DRO-EDL-MPC: Evidential Deep Learning-Based Distributionally Robust Model Predictive Control for Safe Autonomous Driving 提出基于证据深度学习的分布鲁棒模型预测控制,用于安全自动驾驶 MPC model predictive control motion planning
5 Learning to Evaluate Autonomous Behaviour in Human-Robot Interaction 提出NeME,用于评估人机交互中自主行为的模仿学习策略优劣。 humanoid humanoid robot teleoperation
6 Fast Bilateral Teleoperation and Imitation Learning Using Sensorless Force Control via Accurate Dynamics Model 提出基于精确动力学模型的无力传感器四通道遥操作与模仿学习方法 teleoperation imitation learning
7 Hybrid Diffusion Policies with Projective Geometric Algebra for Efficient Robot Manipulation Learning 提出基于射影几何代数的混合扩散策略,提升机器人操作学习效率 manipulation diffusion policy
8 EC-Flow: Enabling Versatile Robotic Manipulation from Action-Unlabeled Videos via Embodiment-Centric Flow EC-Flow:通过具身中心流,从无动作标签视频中实现通用机器人操作 manipulation imitation learning
9 FineGrasp: Towards Robust Grasping for Delicate Objects FineGrasp:面向易损物体的鲁棒抓取方法 manipulation sim-to-real

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

#题目一句话要点标签🔗
10 3DGS_LSR:Large_Scale Relocation for Autonomous Driving Based on 3D Gaussian Splatting 提出基于3D高斯溅射的大规模重定位方法,解决自动驾驶中GNSS失效时的定位问题。 3D gaussian splatting 3DGS gaussian splatting
11 OTAS: Open-vocabulary Token Alignment for Outdoor Segmentation OTAS:面向户外场景分割的开放词汇Token对齐方法 open-vocabulary open vocabulary

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

#题目一句话要点标签🔗
12 Evaluation of Habitat Robotics using Large Language Models 利用大型语言模型评估Habitat机器人解决具身任务的有效性 large language model

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

#题目一句话要点标签🔗
13 LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving LeAD:融合端到端自动驾驶与LLM增强规划系统,解决复杂城市场景问题 imitation learning large language model chain-of-thought

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