Adriano Pinto

Papers

Total Citations

H-Index

About

Adriano Pinto is a researcher in robotics and artificial intelligence, with a primary focus on the application of neural networks for autonomous systems. His most cited work, "Neural control of an autonomous robot" (2014), demonstrates his core contribution: integrating artificial neural networks (ANN) into the control architecture of a robot designed for competitive environments. By testing the robot on arbitrary paths, Pinto validated the effectiveness of neural control in enabling adaptive, real-time navigation without pre-programmed responses. This work, while accumulating 2 citations, lays foundational groundwork for more adaptive robotic behaviors. Pinto's research sits at the intersection of machine learning and autonomous robotics, exploring how bio-inspired computation can replace traditional control logic. His achievements include successfully demonstrating a proof-of-concept that neural networks can govern a robot's decision-making in dynamic settings, a key step toward more intelligent, self-correcting machines. For students and researchers, Pinto's work offers a clear, applied example of how theoretical neural network principles translate into practical robotic control, making it a valuable reference for those entering the field of autonomous systems.