| 1 |
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models |
提出基于分层视觉-语言-动作模型的开放式指令跟随机器人系统 |
dual-arm vision-language-action instruction following |
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| 2 |
ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration |
ObjectVLA:无需演示的端到端开放世界物体操作 |
manipulation dexterous manipulation policy learning |
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| 3 |
Think on your feet: Seamless Transition between Human-like Locomotion in Response to Changing Commands |
提出基于模仿学习的人形机器人运动控制方法,实现复杂指令下的流畅运动过渡 |
humanoid humanoid robot locomotion |
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| 4 |
Stability Analysis of Deep Reinforcement Learning for Multi-Agent Inspection in a Terrestrial Testbed |
提出一种分层深度强化学习框架,用于多智能体卫星自主巡检任务,并在地面测试平台上验证其稳定性。 |
sim-to-real reinforcement learning deep reinforcement learning |
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| 5 |
Hybrid Robot Learning for Automatic Robot Motion Planning in Manufacturing |
提出一种混合强化学习的机器人运动规划方法,用于自动化制造场景。 |
motion planning reinforcement learning deep reinforcement learning |
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| 6 |
Ground-level Viewpoint Vision-and-Language Navigation in Continuous Environments |
提出GVNav,解决低视角机器人视觉语言导航中的泛化性问题 |
quadruped spatiotemporal VLN |
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| 7 |
Attention-Guided Integration of CLIP and SAM for Precise Object Masking in Robotic Manipulation |
提出基于注意力引导的CLIP和SAM集成方法,提升机器人操作中物体掩膜精度 |
manipulation multimodal |
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| 8 |
RL-OGM-Parking: Lidar OGM-Based Hybrid Reinforcement Learning Planner for Autonomous Parking |
提出基于激光雷达OGM和混合强化学习的自动泊车规划器 |
sim-to-real reinforcement learning occupancy grid |
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| 9 |
Surface-Based Manipulation with Modular Foldable Robots |
提出基于表面的模块化折叠机器人操作方法,解决复杂物体操作难题 |
manipulation |
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| 10 |
CPG-Based Manipulation with Multi-Module Origami Robot Surface |
提出基于CPG的多模块折纸机器人表面操作方法,适用于不同尺寸和刚度的物体 |
manipulation |
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| 11 |
Leg Exoskeleton Odometry using a Limited FOV Depth Sensor |
针对腿部外骨骼,提出一种基于有限FOV深度传感器的里程计算法 |
legged robot elevation map |
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| 12 |
Image-Based Roadmaps for Vision-Only Planning and Control of Robotic Manipulators |
提出基于图像的机器人操作臂运动规划方法,无需显式模型和关节编码器 |
motion planning |
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| 13 |
Diffusion-based Planning with Learned Viability Filters |
提出基于扩散模型的学习型可行性过滤器,用于约束运动规划并提升复杂3D运动任务性能。 |
locomotion |
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