3 papers
cs.RO2026
Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback
Jaewoo Lee, Jeongyeon Seo, Sihyun Cho +10
Embodied coding agents construct robot policies from natural-language instructions by generating executable programs and refining them from execution feedback. This refinement assu…
cs.RO2026
Drone Soccer: Learning to Manipulate with Multicopter Downwash
Neelay Joglekar, Bavin Saravanan, Yutong Wang +3
Although multicopter drones are traditionally designed for "perception-only" tasks, like mapping and exploration, recent work has sought to develop Unmanned Aerial Manipulators (UA…
cs.RO2026
AM-Bench: A Modular Simulation Suite and Benchmark for Aerial Manipulation Policy Learning
Yutong Wang, Dongjae Lee, Xiaofeng Guo +9
Standardized benchmarks have played a central role in advancing robot manipulation learning, yet most focus on ground-supported manipulation systems, which limits their applicabili…