6 papers · 1 filter
Deliberate Before You Fly: Vision-Guided Spatial Deliberation for UAV See-and-Reach Navigation
Fanfu Xue, En Yu, Bohang Liu +4
UAV see-and-reach navigation requires an aerial agent to approach a language-specified target visible in its initial view and stop reliably near it. Existing methods typically map…
Push-Wiper: Toward General-Purpose Robotic Cleaning across Varied Stains and Surfaces with Segmented Pushing Trajectories
Renhao Lu, Mingxin Wang, Chenyang Cao +5
Viscous stains, characterized by high viscosity and complex rheological properties, remain a major challenge for robotic surface cleaning. Conventional wiping often spreads the sta…
Stage-Transition Dense Reward Modeling for Reinforcement Learning
Yang Yang, Bingjie Chen, Zihan Wang +4
Reinforcement learning for long-horizon robotic manipulation is often limited by sparse and delayed rewards, while manually designing dense shaping signals is costly and brittle to…
Causal Reward World Models: Zero-shot Reward Design for Automated Skill Generation
Yang Yang, Yuchuang Tong, Zhengtao Zhang +6
Automated Reward Design (ARD) aims to replace manual reward engineering in reinforcement learning with language-driven reward function synthesis. However, existing approaches based…
Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance
Wenhao Wang, Jianheng Song, Chiming Liu +13
While Vision-Language-Action (VLA) models show strong generalizability in various tasks, real-world deployment of robotic policy still requires large-scale, high-quality human expe…
FieldGen: From Teleoperated Pre-Manipulation Trajectories to Field-Guided Data Generation
Wenhao Wang, Kehe Ye, Xinyu Zhou +9
Large-scale and diverse datasets are vital for training robust robotic manipulation policies, yet existing data collection methods struggle to balance scale, diversity, and quality…