Gareth Howells
Papers
12
Total Citations
83
H-Index
6
About
Gareth Howells is a robotics and artificial intelligence researcher whose work centers on assistive mobile robotics, autonomous navigation, and intelligent systems for healthcare applications. His most significant contributions focus on developing smart wheelchair technologies that enhance user safety without compromising personal control — a nuanced challenge that defines much of his research agenda. Howells has made notable advances in collision avoidance systems, including his Dynamic Localized Adjustable Force Field method (2015, 13 citations), which provides real-time assistive navigation for powered wheelchair users. His research into doorway detection and trajectory generation addresses one of the most practical obstacles facing wheelchair users in indoor environments, with multiple papers exploring how autonomous systems can identify and navigate confined spaces effectively. His application of weightless neural networks to real-time robotics represents a particularly innovative thread, demonstrating how computationally efficient architectures can support robust, responsive assistive devices. Beyond wheelchair technology, Howells has contributed to humanoid robot monitoring systems and multi-robot autonomous navigation using potential field algorithms. His 2022 annotated dataset for semantic segmentation underscores an ongoing commitment to building practical, application-driven resources for the research community. Across his career, Howells has consistently prioritized human-centered design, ensuring intelligent systems augment rather than replace human agency.
Research Focus
Key Achievements
Top Papers
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- 5Assistive Trajectories for Human-in-the-Loop Mobile Robotic Platforms6 citations · 2015
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- 7Highly efficient localisation utilising weightless neural systems5 citations · 2012
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