cs.RO(2024-09-10)

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支柱一:机器人控制 (Robot Control) (9 🔗1) 支柱九:具身大模型 (Embodied Foundation Models) (2)

🔬 支柱一:机器人控制 (Robot Control) (9 篇)

#题目一句话要点标签🔗
1 One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion 提出URMA:一种端到端多形态机器人运动学习框架 quadruped legged robot legged locomotion
2 DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots DemoStart:基于演示的自动课程学习,应用于多指机器人模拟到真实环境迁移 manipulation sim-to-real domain randomization
3 Asymptotically Optimal Lazy Lifelong Sampling-based Algorithm for Efficient Motion Planning in Dynamic Environments 提出渐近最优的懒惰终身采样算法以解决动态环境中的路径规划问题 motion planning
4 Human-mimetic binaural ear design and sound source direction estimation for task realization of musculoskeletal humanoids 提出人造双耳听觉系统,用于肌肉骨骼人形机器人实现声音定位与环境感知 humanoid
5 Gait Switching and Enhanced Stabilization of Walking Robots with Deep Learning-based Reachability: A Case Study on Two-link Walker 提出基于深度学习的HJ可达性分析方法,提升双足步行机器人步态切换与稳定控制。 legged robot legged locomotion locomotion
6 One-Shot Imitation under Mismatched Execution RHyME:通过序列级最优传输,实现跨具身单样本模仿学习 manipulation cross-embodiment
7 GeMuCo: Generalized Multisensory Correlational Model for Body Schema Learning 提出广义多感官相关模型(GeMuCo),用于机器人自主学习身体图式 humanoid manipulation
8 Adaptive Electronic Skin Sensitivity for Safe Human-Robot Interaction 提出自适应电子皮肤灵敏度方法,提升人机协作安全性和生产效率。 humanoid
9 Restoration of Reduced Self-Efficacy Caused by Chronic Pain through Manipulated Sensory Discrepancy 提出基于感觉差异操控的方案,旨在恢复慢性疼痛患者的自我效能感。 manipulation

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

#题目一句话要点标签🔗
10 Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles OmniTester:基于多模态大语言模型的自动驾驶场景测试框架 large language model multimodal
11 MAPS: Energy-Reliability Tradeoff Management in Autonomous Vehicles Through LLMs Penetrated Science 提出MAPS:利用LLM提升自动驾驶能耗-可靠性权衡管理 large language model

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