Papers
2
Total Citations
14
H-Index
2
About
Marco Aste is a researcher in robotics and autonomous systems, with a focus on intelligent navigation for mobile robots operating in complex indoor environments. His work bridges the critical gap between high-level mission planning and real-time reactive control, a challenge central to deploying robots in settings like hospitals and shopping malls. In his highly cited 2002 paper, Aste introduced a layered architecture that enables robots to dynamically balance strategic goals with immediate sensor-driven responses, a foundational contribution to autonomous indoor navigation. He further advanced the field by applying radial basis function networks (RBFNs) to teach robots how to learn navigation behaviors directly from visual inputs, as detailed in his 2003 work. This learning-based approach reduces the need for hand-coded rules, allowing robots to adapt to new environments more flexibly. Though his citation counts are modest, Aste’s research represents an important step toward practical, self-sufficient mobile robots, combining classical planning with modern machine learning techniques. His work remains relevant for students and engineers developing robust navigation systems for real-world service robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2