Jacson Rodrigues Correia da Silva
Papers
1
Total Citations
7
H-Index
1
About
Jacson Rodrigues Correia da Silva has made significant contributions to the field of robotics and intelligent systems, with a particular focus on autonomous vehicle simulation and control. His most cited work, "Simulating robotic cars using time-delay neural networks" (2016, 7 citations), introduces a novel approach to modeling the dynamics of robotic cars by employing two time-delay neural networks. These networks simulate how effort commands influence a vehicle's velocity and direction, offering a robust framework for understanding and predicting autonomous motion. This research is foundational for developing more realistic and efficient robotic car simulators, which are crucial for testing and training autonomous systems without physical prototypes. Jacson's work bridges the gap between neural network theory and practical robotics, demonstrating how time-delay architectures can capture temporal dependencies in vehicle control. His contributions are particularly valuable for students and researchers interested in autonomous navigation, neural network applications, and simulation-based robotics. With a growing citation impact, Jacson Rodrigues Correia da Silva continues to influence the development of intelligent, self-driving technologies.
Research Focus
Key Achievements
Top Papers
- 1Simulating robotic cars using time-delay neural networks7 citations · 2016