Xavier Jonathon Blake

Papers

Total Citations

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About

Xavier Jonathon Blake’s research centers on the intersection of neural network architectures and classical control theory, with a particular focus on autonomous mobile robotics. His most cited work, “PID Control for a Path-Following Error-Producing Neural Network,” introduces a novel methodology that integrates a neural network with a PID controller to enable a three-wheeled differential robot to autonomously follow a predefined path. By feeding pre-processed path images through the network to generate error signals for the controller, Blake’s approach bridges the gap between machine learning and traditional control systems, offering a practical solution for real-time navigation. Despite accumulating only 2 citations to date, this paper represents a foundational step in his exploration of error-driven neural control mechanisms. Blake’s contributions are notable for their emphasis on simplicity and efficiency, aiming to reduce computational overhead while maintaining robust path-following performance. His work holds promise for applications in warehouse logistics, autonomous inspection, and educational robotics, where reliable low-cost navigation is critical. As an emerging researcher, Blake continues to refine his hybrid control strategies, positioning himself at the forefront of integrating neural networks with classical engineering principles.