This paper introduces Stage-Aware Reinforcement (StARe), a novel module that decomposes long-horizon robotic manipulation tasks into semantically meaningful stages, providing dense, interpretable reinforcement signals. Integrated into the Imitation → Preference → Interaction (IPI) fine-tuning pipeline, StARe significantly improves the performance and robustness of Vision-Language-Action (VLA) models on complex manipulation tasks.

This paper introduces a modular architecture for autonomous vehicles designed for racing in closed circuits. It integrates perception, localization, path planning, and control subsystems to achieve real-time, precise autonomous navigation in controlled environments.

This paper introduces "Artificial Microsaccade Compensation," a real-time video stabilization method inspired by biological microsaccades. It enables stable camera-based perception for aggressively shaking tailless ornithopters, a significant challenge for autonomous flapping-wing robots.