cs.RO（2025-07-29）

📊 共 11 篇论文 | 🔗 1 篇有代码

🎯 兴趣领域导航

支柱一：机器人控制 (Robot Control) (8 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (1) 支柱九：具身大模型 (Embodied Foundation Models) (1) 支柱三：空间感知与语义 (Perception & Semantics) (1)

🔬 支柱一：机器人控制 (Robot Control) (8 篇)

#题目一句话要点标签🔗⭐
1 A Nonlinear MPC Framework for Loco-Manipulation of Quadrupedal Robots with Non-Negligible Manipulator Dynamics 提出一种非线性MPC框架，用于解决四足机器人非轻量级机械臂的协同操作控制问题。 quadruped legged robot legged locomotion
2 MoDeSuite: Robot Learning Task Suite for Benchmarking Mobile Manipulation with Deformable Objects MoDeSuite：用于柔性物体移动操作机器人学习任务基准套件 manipulation mobile manipulation sim-to-real
3 DISCOVERSE: Efficient Robot Simulation in Complex High-Fidelity Environments DISCOVERSE：基于3DGS的高效高保真机器人仿真框架，用于Real2Sim2Real机器人学习。 sim2real real2sim imitation learning ✅
4 Model Predictive Adversarial Imitation Learning for Planning from Observation 提出基于模型预测的对抗模仿学习方法，用于从观察数据中进行规划。 MPC model predictive control reinforcement learning
5 A Systematic Robot Design Optimization Methodology with Application to Redundant Dual-Arm Manipulators 提出一种系统性机器人设计优化方法，应用于冗余双臂采摘机器人。 manipulation dual-arm
6 Pretraining a Unified PDDL Domain from Real-World Demonstrations for Generalizable Robot Task Planning UniDomain：预训练统一PDDL领域，提升机器人任务规划的泛化性 manipulation symbolic grounding
7 emg2tendon: From sEMG Signals to Tendon Control in Musculoskeletal Hands 提出emg2tendon数据集与扩散回归模型，实现肌电信号到肌腱控制的精准映射 manipulation
8 LITE: A Learning-Integrated Topological Explorer for Multi-Floor Indoor Environments LITE：一种学习融合的拓扑探索器，用于多楼层室内环境探索 quadruped

🔬 支柱二：RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗⭐
9 Decision Transformer-Based Drone Trajectory Planning with Dynamic Safety-Efficiency Trade-Offs 提出基于Decision Transformer的无人机轨迹规划器，实现动态安全-效率权衡。 reinforcement learning decision transformer

🔬 支柱九：具身大模型 (Embodied Foundation Models) (1 篇)

#题目一句话要点标签🔗⭐
10 Multifunctional physical reservoir computing in soft tensegrity robots 利用软体张拉整体机器人的物理储层计算实现多功能控制 embodied AI

🔬 支柱三：空间感知与语义 (Perception & Semantics) (1 篇)

#题目一句话要点标签🔗⭐
11 A Survey on Deep Multi-Task Learning in Connected Autonomous Vehicles 综述：面向车联网自动驾驶车辆的深度多任务学习研究 depth estimation

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