cs.RO(2024-10-18)
📊 共 10 篇论文
🎯 兴趣领域导航
支柱一:机器人控制 (Robot Control) (5)
支柱三:空间感知与语义 (Perception & Semantics) (2)
支柱二:RL算法与架构 (RL & Architecture) (2)
支柱九:具身大模型 (Embodied Foundation Models) (1)
🔬 支柱一:机器人控制 (Robot Control) (5 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | Diff-DAgger: Uncertainty Estimation with Diffusion Policy for Robotic Manipulation | Diff-DAgger:利用扩散策略的不确定性估计提升机器人操作的交互式模仿学习效率。 | manipulation imitation learning diffusion policy | ||
| 2 | Sim2real Cattle Joint Estimation in 3D point clouds | 提出基于曲率和测地距离的牛体三维点云关节估计方法,缩小Sim2Real差距。 | sim2real | ||
| 3 | Learning autonomous driving from aerial imagery | 提出基于NeRF的端到端自动驾驶学习方法,仅使用航拍图像。 | sim-to-real NeRF neural radiance field | ||
| 4 | A Probabilistic Model for Skill Acquisition with Switching Latent Feedback Controllers | 提出基于切换隐反馈控制器的概率模型,提升机器人技能学习的鲁棒性。 | manipulation | ||
| 5 | Skill Generalization with Verbs | 提出基于动词的技能泛化方法,实现机器人对新物体的操作技能学习 | manipulation |
🔬 支柱三:空间感知与语义 (Perception & Semantics) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 6 | GS-LIVM: Real-Time Photo-Realistic LiDAR-Inertial-Visual Mapping with Gaussian Splatting | GS-LIVM:基于高斯溅射的实时照片级真实感激光雷达-惯性-视觉建图 | 3D gaussian splatting 3DGS gaussian splatting | ||
| 7 | IntelliMove: Enhancing Robotic Planning with Semantic Mapping | IntelliMove:提出基于语义地图的机器人规划框架,提升导航效率与语义任务能力 | semantic mapping semantic map |
🔬 支柱二:RL算法与架构 (RL & Architecture) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 8 | Benchmarking Deep Reinforcement Learning for Navigation in Denied Sensor Environments | 针对传感器失效环境,提出基于对抗训练的DreamerV3导航基准 | reinforcement learning deep reinforcement learning DRL | ||
| 9 | MARLIN: Multi-Agent Reinforcement Learning Guided by Language-Based Inter-Robot Negotiation | MARLIN:基于语言协商的多智能体强化学习,加速机器人训练 | reinforcement learning 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 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 10 | Coherence-Driven Multimodal Safety Dialogue with Active Learning for Embodied Agents | 提出M-CoDAL,利用连贯性驱动的多模态对话系统提升具身智能体在安全场景下的交互能力。 | large language model multimodal |