Brian Wright

Max Planck Institute for Intelligent Systems

Papers

Total Citations

H-Index

About

Brian Wright is a leading researcher in bio-inspired soft robotics, with a particular focus on underwater locomotion and sensing. His work bridges the gap between biology and engineering, using soft robotic platforms to experimentally investigate how animals like fish modulate body stiffness to achieve efficient undulatory swimming. Wright’s most-cited paper, "Soft Sensors for Curvature Estimation under Water in a Soft Robotic Fish" (2019), introduced a novel biorobotic model that employs soft bending actuators to replicate and measure lateral body motion in real time. This contribution has been cited 17 times and is foundational for researchers exploring adaptive locomotion in unstructured aquatic environments. Beyond this, Wright has advanced the integration of soft sensors for real-time curvature estimation, enabling more precise control and feedback in deformable robotic systems. His work not only deepens our understanding of biological propulsion but also informs the design of resilient, fish-inspired robots for environmental monitoring and exploration. Wright’s research is essential reading for anyone interested in the intersection of soft materials, bio-inspired design, and underwater robotics.