English

AnyUser: Translating Sketched User Intent into Domestic Robots

Robotics 2026-04-07 v1 Computer Vision and Pattern Recognition Human-Computer Interaction

Abstract

We introduce AnyUser, a unified robotic instruction system for intuitive domestic task instruction via free-form sketches on camera images, optionally with language. AnyUser interprets multimodal inputs (sketch, vision, language) as spatial-semantic primitives to generate executable robot actions requiring no prior maps or models. Novel components include multimodal fusion for understanding and a hierarchical policy for robust action generation. Efficacy is shown via extensive evaluations: (1) Quantitative benchmarks on the large-scale dataset showing high accuracy in interpreting diverse sketch-based commands across various simulated domestic scenes. (2) Real-world validation on two distinct robotic platforms, a statically mounted 7-DoF assistive arm (KUKA LBR iiwa) and a dual-arm mobile manipulator (Realman RMC-AIDAL), performing representative tasks like targeted wiping and area cleaning, confirming the system's ability to ground instructions and execute them reliably in physical environments. (3) A comprehensive user study involving diverse demographics (elderly, simulated non-verbal, low technical literacy) demonstrating significant improvements in usability and task specification efficiency, achieving high task completion rates (85.7%-96.4%) and user satisfaction. AnyUser bridges the gap between advanced robotic capabilities and the need for accessible non-expert interaction, laying the foundation for practical assistive robots adaptable to real-world human environments.

Keywords

Cite

@article{arxiv.2604.04811,
  title  = {AnyUser: Translating Sketched User Intent into Domestic Robots},
  author = {Songyuan Yang and Huibin Tan and Kailun Yang and Wenjing Yang and Shaowu Yang},
  journal= {arXiv preprint arXiv:2604.04811},
  year   = {2026}
}

Comments

Accepted to IEEE Transactions on Robotics (T-RO)

R2 v1 2026-07-01T11:55:30.701Z