Papers
5
Total Citations
27
H-Index
5
About
Marco Visca is a robotics researcher specializing in autonomous mobile robot navigation, energy-aware path planning, and machine learning applications for unstructured terrain traversal. His work addresses one of the most pressing challenges in field robotics: enabling robots to operate efficiently and independently in complex off-road environments where power resources are limited and terrain conditions are unpredictable. Visca's most significant contributions center on developing novel deep learning frameworks — particularly Conv1D and Meta-Conv1D architectures — that allow robots to estimate driving energy consumption in real time without sacrificing accuracy. His probabilistic approaches further advance this area by quantifying uncertainty in energy predictions, a critical consideration when terrain properties are constantly varying and difficult to model. Complementing this work, his research on deep learning-based traversability estimation equips robots with the ability to assess which terrain regions are safely and efficiently navigable. With citations accumulating across multiple publications from 2021 and 2022, Visca's research is gaining recognition within the robotics and autonomous systems community. His integrated approach — combining energy modeling, probabilistic reasoning, and traversability assessment — positions him as an emerging voice in the design of intelligent, energy-conscious navigation systems for next-generation autonomous robots operating in challenging real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5