Thomas C. Knowles
Bristol Robotics Laboratory, University of the West of England
Papers
3
Total Citations
27
H-Index
3
About
Thomas C. Knowles is a researcher at the intersection of robotics, neuroscience, and artificial intelligence, whose work focuses on biomimetic navigation and multimodal perception. His primary research areas include place recognition, spatial memory, and neural network architectures inspired by biological systems. Knowles’s most cited work, “Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding” (2021, 21 citations), introduces a novel framework that fuses sensory data from multiple modalities—such as vision and touch—to improve robustness in robot navigation, addressing critical challenges in data registration and dimensionality. This contribution is foundational for developing autonomous systems that operate reliably in real-world environments. His other notable studies, including “WhiskEye: A Biomimetic Model of Multisensory Spatial Memory” and “Ring Attractors as the Basis of a Biomimetic Navigation System” (2023), further explore how neural structures like ring attractor networks can be modeled using spiking neural networks to replicate animal navigation capabilities. By bridging computational models with biological principles, Knowles’s work offers innovative pathways for creating more adaptive and efficient robotic systems, making him a rising voice in embodied AI and neurorobotics.
Research Focus
Key Achievements
Top Papers
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- 3Ring Attractors as the Basis of a Biomimetic Navigation System3 citations · 2023