cs.RO（2023-10-16）

📊 共 13 篇论文 | 🔗 3 篇有代码

🎯 兴趣领域导航

支柱一：机器人控制 (Robot Control) (8 🔗2) 支柱二：RL算法与架构 (RL & Architecture) (2) 支柱九：具身大模型 (Embodied Foundation Models) (2 🔗1) 支柱七：动作重定向 (Motion Retargeting) (1)

🔬 支柱一：机器人控制 (Robot Control) (8 篇)

#题目一句话要点标签🔗⭐
1 ManyQuadrupeds: Learning a Single Locomotion Policy for Diverse Quadruped Robots 提出一种单一运动策略以解决多样化四足机器人控制问题 quadruped locomotion locomotion policy
2 RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models 提出RoboLLM以解决机器人视觉任务集成问题 manipulation large language model multimodal ✅
3 Efficient Sim-to-real Transfer of Contact-Rich Manipulation Skills with Online Admittance Residual Learning 提出混合离线-在线框架以解决接触丰富的操作技能学习问题 manipulation sim-to-real domain randomization
4 Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models 提出SuSIE以解决零样本机器人操作问题 manipulation privileged information language conditioned ✅
5 BayRnTune: Adaptive Bayesian Domain Randomization via Strategic Fine-tuning 提出BayRnTune以加速自适应贝叶斯领域随机化 legged robot domain randomization
6 Temporally Robust Multi-Agent STL Motion Planning in Continuous Time 提出基于连续时间的多智能体STL运动规划以增强时间鲁棒性 motion planning
7 Manta Ray Inspired Flapping-Wing Blimp 提出一种基于曼塔鱼的拍翼飞艇以提升飞行效率 locomotion
8 Learning visual-based deformable object rearrangement with local graph neural networks 提出局部图神经网络以解决可变形物体重排问题 manipulation

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

#题目一句话要点标签🔗⭐
9 Bootstrap Your Own Skills: Learning to Solve New Tasks with Large Language Model Guidance 提出BOSS方法以解决复杂任务学习问题 reinforcement learning large language model
10 Vision and Language Navigation in the Real World via Online Visual Language Mapping 提出一种新框架以解决真实环境中的视觉语言导航问题 PPO VLN foundation model

🔬 支柱九：具身大模型 (Embodied Foundation Models) (2 篇)

#题目一句话要点标签🔗⭐
11 Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning 提出语言前沿引导方法以优化机器人导航问题 large language model
12 Interactive Task Planning with Language Models 提出一种交互式任务规划框架以解决传统方法的局限性 large language model ✅

🔬 支柱七：动作重定向 (Motion Retargeting) (1 篇)

#题目一句话要点标签🔗⭐
13 A Human Motion Compensation Framework for a Supernumerary Robotic Arm 提出人类运动补偿框架以解决超数目机器人臂的干扰问题 human motion

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