cs.RO（2024-02-07）

📊 共 14 篇论文 | 🔗 1 篇有代码

🎯 兴趣领域导航

支柱一：机器人控制 (Robot Control) (6) 支柱二：RL算法与架构 (RL & Architecture) (4 🔗1) 支柱三：空间感知与语义 (Perception & Semantics) (2) 支柱九：具身大模型 (Embodied Foundation Models) (2)

🔬 支柱一：机器人控制 (Robot Control) (6 篇)

#	题目	一句话要点	标签	🔗	⭐
1	ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation	提出ALOHA 2以提升双手遥操作的性能与易用性	manipulation bi-manual bimanual manipulation
2	Smooth real-time motion planning based on a cascade dual-quaternion screw-geometry MPC	提出基于级联双四元数螺旋几何的运动规划方法以解决平滑轨迹跟踪问题	MPC motion planning
3	Offline Deep Model Predictive Control (MPC) for Visual Navigation	提出基于离线深度模型预测控制的视觉导航方法	MPC model predictive control
4	Hierarchical Motion Planning and Offline Robust Model Predictive Control for Autonomous Vehicles	提出层次化运动规划与鲁棒控制策略以应对复杂驾驶场景	model predictive control motion planning
5	Model Predictive Trajectory Optimization With Dynamically Changing Waypoints for Serial Manipulators	提出动态变化路径点的模型预测轨迹优化方法以解决在线规划问题	model predictive control trajectory optimization
6	Entanglement Definitions for Tethered Robots: Exploration and Analysis	提出新的缆绳纠缠定义以解决缆绳移动机器人问题	motion planning

🔬 支柱二：RL算法与架构 (RL & Architecture) (4 篇)

#	题目	一句话要点	标签	🔗	⭐
7	Mobile Robot Exploration Without Maps via Out-of-Distribution Deep Reinforcement Learning	提出无地图自主移动机器人探索方法以解决动态环境导航问题	reinforcement learning deep reinforcement learning DRL
8	Deep Reinforcement Learning with Dynamic Graphs for Adaptive Informative Path Planning	提出动态图深度强化学习以解决自适应信息路径规划问题	reinforcement learning deep reinforcement learning	✅
9	Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation	提出语言增强方法以解决目标导航中的快捷学习问题	reinforcement learning deep reinforcement learning DRL
10	Boosting Reinforcement Learning Algorithms in Continuous Robotic Reaching Tasks using Adaptive Potential Functions	提出自适应势能函数以提升连续机器人到达任务的强化学习算法	reinforcement learning reward shaping

🔬 支柱三：空间感知与语义 (Perception & Semantics) (2 篇)

#	题目	一句话要点	标签	🔗	⭐
11	Online and Certifiably Correct Visual Odometry and Mapping	提出认证视觉里程计与映射算法以解决安全关键型机器人感知问题	visual odometry
12	InCoRo: In-Context Learning for Robotics Control with Feedback Loops	提出InCoRo以解决动态环境下机器人控制问题	scene understanding

🔬 支柱九：具身大模型 (Embodied Foundation Models) (2 篇)

#	题目	一句话要点	标签	🔗	⭐
13	A Comprehensive Survey of Cross-Domain Policy Transfer for Embodied Agents	系统评估跨域策略迁移以应对数据不足问题	embodied AI
14	Tactile-based Object Retrieval From Granular Media	提出GEOTACT以解决颗粒介质中物体检索问题	zero-shot transfer

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