| 1 |
Bunny-VisionPro: Real-Time Bimanual Dexterous Teleoperation for Imitation Learning |
Bunny-VisionPro：用于模仿学习的实时双手动灵巧遥操作系统 |
manipulation dexterous hand dexterous manipulation |
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| 2 |
TieBot: Learning to Knot a Tie from Visual Demonstration through a Real-to-Sim-to-Real Approach |
TieBot：提出一种基于视觉演示的Real-to-Sim-to-Real方法，用于机器人学习打领带 |
manipulation dual-arm sim-to-real |
✅ |
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| 3 |
PPO-based Dynamic Control of Uncertain Floating Platforms in the Zero-G Environment |
提出基于PPO-MPC的零重力环境不确定浮动平台动态控制方法 |
MPC model predictive control reinforcement learning |
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| 4 |
PWTO: A Heuristic Approach for Trajectory Optimization in Complex Terrains |
PWTO：一种复杂地形下机器人轨迹优化的启发式方法 |
quadruped trajectory optimization |
✅ |
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| 5 |
Solving Motion Planning Tasks with a Scalable Generative Model |
提出一种可扩展的生成模型，用于解决自动驾驶中的运动规划任务。 |
motion planning reinforcement learning |
✅ |
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| 6 |
Online Time-Informed Kinodynamic Motion Planning of Nonlinear Systems |
提出基于深度学习的在线时间启发运动规划方法，加速非线性系统运动规划。 |
motion planning |
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| 7 |
OrbitGrasp: $SE(3)$-Equivariant Grasp Learning |
提出OrbitGrasp，一种SE(3)等变抓取学习框架，提升非结构化环境下的机器人抓取性能。 |
manipulation |
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| 8 |
Learning deformable linear object dynamics from a single trajectory |
提出一种基于物理信息的神经ODE，仅用少量数据学习可变形线性物体动力学。 |
manipulation |
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| 9 |
NLP Sampling: Combining MCMC and NLP Methods for Diverse Constrained Sampling |
提出NLP采样框架，结合MCMC与NLP方法，解决带约束的多样性采样问题 |
manipulation |
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| 10 |
The Shortcomings of Force-from-Motion in Robot Learning |
指出机器人学习中基于运动推导力方法的局限性，倡导交互显式的动作空间 |
manipulation |
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