Papers
6
Total Citations
103
H-Index
5
About
James Brett is a researcher specializing in soft robotics, with a particular focus on jamming-based mechanisms, compliant robotic systems, and computational design methodologies. His work has made significant contributions to the development of soft robotic grippers and actuators, combining innovative fabrication techniques with intelligent design frameworks to push the boundaries of what compliant robots can achieve. Brett's most influential contribution, "One-Shot 3D-Printed Multimaterial Soft Robotic Jamming Grippers" (2021, 47 citations), demonstrated how multi-material 3D printing could dramatically streamline the fabrication of high-performance soft grippers. Building on this, his exploration of granular and fibre jamming technologies — including the novel "Jammkle" robotic ankle (11 citations) and fibre-jammed compliant leg designs — has broadened the applicability of jamming mechanisms beyond gripping into dynamic locomotion and bio-inspired robotics. His development of Fin-Bayes, a multi-objective Bayesian optimization framework for soft robotic fingers (2024, 13 citations), reflects a growing emphasis on computational design tools that accelerate innovation in the field. With over 100 cumulative citations, Brett's research is establishing a cohesive vision for the future of soft robotics — one where smart fabrication, adaptive morphology, and principled optimization converge to create truly capable compliant machines.
Research Focus
Key Achievements
Top Papers
- 1One-Shot 3D-Printed Multimaterial Soft Robotic Jamming Grippers47 citations · 2021
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- 5A Compliant Robotic Leg Based on Fibre Jamming10 citations · 2024
- 6Active Vibration Fluidization for Granular Jamming Grippers4 citations · 2023