cs.RO(2024-06-03)

📊 共 14 篇论文

🎯 兴趣领域导航

支柱一:机器人控制 (Robot Control) (7) 支柱九:具身大模型 (Embodied Foundation Models) (3) 支柱七:动作重定向 (Motion Retargeting) (2) 支柱二:RL算法与架构 (RL & Architecture) (1) 支柱五:交互与反应 (Interaction & Reaction) (1)

🔬 支柱一:机器人控制 (Robot Control) (7 篇)

#题目一句话要点标签🔗
1 Learning-based legged locomotion; state of the art and future perspectives 基于学习的足式机器人运动控制:现状与未来展望 quadruped legged locomotion humanoid
2 PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planning 提出PlanAgent,基于多模态大语言模型解决自动驾驶闭环运动规划问题 motion planning scene understanding large language model
3 ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation ManiCM:基于一致性模型的实时3D扩散策略,用于机器人操作 manipulation diffusion policy distillation
4 Motion Planning for Hybrid Dynamical Systems: Framework, Algorithm Template, and a Sampling-based Approach 提出一种基于RRT的混合动力系统运动规划算法HyRRT,解决复杂系统运动规划问题。 motion planning
5 Provably Feasible and Stable White-Box Trajectory Optimization 提出白盒轨迹优化方法,解决强约束动态系统的可行性和稳定性问题 trajectory optimization
6 Configuration Space Distance Fields for Manipulation Planning 提出基于配置空间距离场(CDF)的机器人操作规划方法,实现高效避障与运动优化。 manipulation
7 Walk on Spheres for PDE-based Path Planning 探索基于PDE的Walk on Spheres算法在机器人路径规划中的应用 motion planning

🔬 支柱九:具身大模型 (Embodied Foundation Models) (3 篇)

#题目一句话要点标签🔗
8 Ubiquitous Robot Control Through Multimodal Motion Capture Using Smartwatch and Smartphone Data 提出WearMoCap,利用智能手表和手机进行无缝机器人控制的多模态运动捕捉开源库。 multimodal
9 HBTP: Heuristic Behavior Tree Planning with Large Language Model Reasoning 提出HBTP框架,结合LLM推理与行为树规划,提升机器人任务规划效率与可靠性 large language model
10 ZAPP! Zonotope Agreement of Prediction and Planning for Continuous-Time Collision Avoidance with Discrete-Time Dynamics ZAPP:基于Zonotope一致性的预测与规划,解决连续时间碰撞避免问题 multimodal

🔬 支柱七:动作重定向 (Motion Retargeting) (2 篇)

#题目一句话要点标签🔗
11 A Robust Filter for Marker-less Multi-person Tracking in Human-Robot Interaction Scenarios 提出一种鲁棒的滤波方法,用于人机交互场景中无标记多人跟踪 motion representation
12 Region-aware Grasp Framework with Normalized Grasp Space for Efficient 6-DoF Grasping 提出基于归一化抓取空间的区域感知抓取框架,高效解决复杂场景下的6自由度抓取问题 human-to-robot

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

#题目一句话要点标签🔗
13 Evaluating MEDIRL: A Replication and Ablation Study of Maximum Entropy Deep Inverse Reinforcement Learning for Human Social Navigation 改进MEDIRL用于人机交互,优化人群环境中行人行为建模 reinforcement learning inverse reinforcement learning

🔬 支柱五:交互与反应 (Interaction & Reaction) (1 篇)

#题目一句话要点标签🔗
14 Hybrid Quadratic Programming -- Pullback Bundle Dynamical Systems Control 提出混合二次规划的拉回丛动力系统控制方法,用于机器人自适应运动。 reactive motion

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