From the 1 of 6 linked papers with an AI index.
6 papers
HiFi-UMI: Learning Deployable Manipulation Policies from High-Fidelity UMI Data Alone
Simple AI, :, Yuteng Wei +16
Learning deployable manipulation policies is bottlenecked by the scarcity of data that is both high-fidelity and scalable. Real-robot teleoperation is accurate but costly to scale;…
Diagnosing Semantic Handoff Failures in Agent-Orchestrated Vision-Language-Action Skill Composition
Ke Rui, Yushen Zuo, Jiawei Wang +4
The paper investigates why robots fail when chaining language‑conditioned skills for long‑horizon household tasks, introducing a vision‑language‑action harness that checks skill ch…
Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation
Yihao Wu, Jinming Ma, Junbo Tan +5
Diffusion-based policies generalize poorly in semantic manipulation, a key obstacle to real-world deployment, because text-only instructions cannot reliably steer the policy toward…
Learning Diverse Skills for Behavior Models with Mixture of Experts
Wangtian Shen, Jinming Ma, Mingliang Zhou +1
Imitation learning has demonstrated strong performance in robotic manipulation by learning from large-scale human demonstrations. While existing models excel at single-task learnin…
An Efficient and Multi-Modal Navigation System with One-Step World Model
Wangtian Shen, Ziyang Meng, Jinming Ma +2
Navigation is a fundamental capability for mobile robots. While the current trend is to use learning-based approaches to replace traditional geometry-based methods, existing end-to…
Reinforced Embodied Planning with Verifiable Reward for Real-World Robotic Manipulation
Zitong Bo, Yue Hu, Jinming Ma +7
Enabling robots to execute long-horizon manipulation tasks from free-form language instructions remains a fundamental challenge in embodied AI. While vision-language models (VLMs)…