| 1 |
DemoHLM: From One Demonstration to Generalizable Humanoid Loco-Manipulation |
DemoHLM:基于单次模拟演示实现通用人形机器人移动操作 |
humanoid humanoid robot whole-body control |
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| 2 |
NaviGait: Navigating Dynamically Feasible Gait Libraries using Deep Reinforcement Learning |
NaviGait:利用深度强化学习导航动态可行步态库,实现稳健的双足机器人运动控制。 |
bipedal biped locomotion |
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| 3 |
Phys2Real: Fusing VLM Priors with Interactive Online Adaptation for Uncertainty-Aware Sim-to-Real Manipulation |
Phys2Real:融合VLM先验与交互式在线自适应,实现不确定性感知的Sim-to-Real操作 |
manipulation sim-to-real domain randomization |
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| 4 |
Ego-Vision World Model for Humanoid Contact Planning |
提出基于自中心视觉世界模型的类人机器人接触规划方法 |
humanoid humanoid robot MPC |
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| 5 |
Path and Motion Optimization for Efficient Multi-Location Inspection with Humanoid Robots |
提出一种高效的人形机器人多点巡检路径与运动优化框架 |
humanoid humanoid robot MPC |
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| 6 |
Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey |
机器人操作的统一理解:全面的综述,涵盖方法、瓶颈与应用。 |
manipulation policy learning affordance |
✅ |
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| 7 |
ManiAgent: An Agentic Framework for General Robotic Manipulation |
ManiAgent:一种用于通用机器人操作的Agent框架,解决复杂推理和长时程任务规划问题。 |
manipulation vision-language-action VLA |
✅ |
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| 8 |
Simultaneous Calibration of Noise Covariance and Kinematics for State Estimation of Legged Robots via Bi-level Optimization |
提出双层优化框架,同步标定腿式机器人状态估计中的噪声协方差与运动学参数 |
quadruped legged robot humanoid |
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| 9 |
PhysHSI: Towards a Real-World Generalizable and Natural Humanoid-Scene Interaction System |
PhysHSI:面向真实世界可泛化和自然的人形机器人场景交互系统 |
humanoid humanoid robot policy learning |
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| 10 |
Constraint-Aware Reinforcement Learning via Adaptive Action Scaling |
提出基于自适应动作缩放的约束感知强化学习方法,提升安全性和性能。 |
locomotion reinforcement learning SAC |
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| 11 |
A Modular AIoT Framework for Low-Latency Real-Time Robotic Teleoperation in Smart Cities |
提出基于AIoT的模块化低延迟机器人遥操作框架,应用于智慧城市。 |
manipulation teleoperation |
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| 12 |
Design and Koopman Model Predictive Control of A Soft Exoskeleton Based on Origami-Inspired Pneumatic Actuator for Knee Rehabilitation |
提出基于折纸气动软体外骨骼的Koopman模型预测控制方法,用于膝关节康复。 |
MPC model predictive control |
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| 13 |
More than A Point: Capturing Uncertainty with Adaptive Affordance Heatmaps for Spatial Grounding in Robotic Tasks |
RoboMAP:提出自适应Affordance热图,提升机器人空间定位任务的鲁棒性与效率 |
manipulation affordance |
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| 14 |
HiMaCon: Discovering Hierarchical Manipulation Concepts from Unlabeled Multi-Modal Data |
HiMaCon:从无标注多模态数据中发现分层操作概念,提升机器人操作泛化性 |
manipulation representation learning |
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| 15 |
Unveiling Uncertainty-Aware Autonomous Cooperative Learning Based Planning Strategy |
提出基于不确定性感知的自主协同学习规划策略,提升多车交互的安全性和有效性。 |
motion planning reinforcement learning deep reinforcement learning |
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| 16 |
SCOOP'D: Learning Mixed-Liquid-Solid Scooping via Sim2Real Generative Policy |
SCOOP'D:基于Sim2Real生成策略学习混合液体-固体抓取 |
sim2real |
✅ |
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| 17 |
Into the Unknown: Towards using Generative Models for Sampling Priors of Environment Uncertainty for Planning in Configuration Spaces |
提出基于生成模型的采样方法,用于配置空间规划中环境不确定性的先验估计。 |
motion planning |
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| 18 |
An Adaptive Transition Framework for Game-Theoretic Based Takeover |
提出基于博弈论的自适应过渡框架,优化自动驾驶系统中的控制权切换 |
shared control |
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