| 1 |
Model-Based Lookahead Reinforcement Learning for in-hand manipulation |
提出基于模型的预测强化学习方法,提升灵巧手操作性能 |
manipulation in-hand manipulation model predictive control |
|
|
| 2 |
HANDO: Hierarchical Autonomous Navigation and Dexterous Omni-loco-manipulation |
提出HANDO框架,实现腿式机器人自主导航与灵巧全方位移动操作 |
legged robot whole-body control manipulation |
|
|
| 3 |
Glovity: Learning Dexterous Contact-Rich Manipulation via Spatial Wrench Feedback Teleoperation System |
Glovity:基于空间力/力矩反馈遥操作系统学习灵巧的接触丰富操作 |
manipulation dexterous manipulation teleoperation |
|
|
| 4 |
Enhancing Diffusion Policy with Classifier-Free Guidance for Temporal Robotic Tasks |
提出基于无分类器引导的扩散策略CFG-DP,提升时序机器人任务性能 |
humanoid humanoid robot diffusion policy |
|
|
| 5 |
Dynamic Quadrupedal Legged and Aerial Locomotion via Structure Repurposing |
提出一种基于结构重用的动态四足腿式与飞行运动融合方案 |
quadruped legged locomotion locomotion |
|
|
| 6 |
PLEXUS Hand: Lightweight Four-Motor Prosthetic Hand Enabling Precision-Lateral Dexterous Manipulation |
PLEXUS Hand:轻量化四电机假肢手,实现精确横向灵巧操作 |
manipulation dexterous manipulation in-hand manipulation |
|
|
| 7 |
iMoWM: Taming Interactive Multi-Modal World Model for Robotic Manipulation |
提出iMoWM,利用交互式多模态世界模型提升机器人操作能力 |
manipulation reinforcement learning imitation learning |
✅ |
|
| 8 |
Guiding Energy-Efficient Locomotion through Impact Mitigation Rewards |
通过冲击缓解奖励引导能量高效的机器人运动 |
locomotion reinforcement learning imitation learning |
|
|
| 9 |
Flow-Opt: Scalable Centralized Multi-Robot Trajectory Optimization with Flow Matching and Differentiable Optimization |
Flow-Opt:基于流匹配和可微优化的可扩展集中式多机器人轨迹优化 |
trajectory optimization flow matching |
|
|
| 10 |
Obstacle Avoidance using Dynamic Movement Primitives and Reinforcement Learning |
提出基于DMP和强化学习的避障方法,仅需单次演示即可快速生成平滑轨迹。 |
motion planning reinforcement learning |
✅ |
|
| 11 |
Bridging Research and Practice in Simulation-based Testing of Industrial Robot Navigation Systems |
Surrealist框架:基于仿真的工业机器人导航系统测试与验证 |
quadruped ANYmal |
|
|
| 12 |
Real-time Mixed-Integer Quadratic Programming for Driving Behavior-Inspired Speed Bump Optimal Trajectory Planning |
提出基于MIQP的实时轨迹规划方法,解决自动驾驶车辆通过减速带时的舒适性问题。 |
MPC model predictive control |
|
|
| 13 |
When a Robot is More Capable than a Human: Learning from Constrained Demonstrators |
利用受限示教者数据,机器人学习超越人类能力的策略 |
sim-to-real imitation learning |
|
|
| 14 |
Parametrized Topological Complexity for a Multi-Robot System with Variable Tasks |
针对多机器人变任务系统,提出参数化拓扑复杂度的运动规划方法 |
motion planning |
|
|