Jordan M. Thompson
Papers
2
Total Citations
10
H-Index
2
About
Jordan M. Thompson is a rising researcher in the field of soft and continuum robotics, with a focus on the modeling and control of tendon-driven continuum robots for medical applications. His major contribution lies in addressing the critical challenge of hysteresis—the lag between input and output motion—in nonlinearly-routed tendon-driven systems. In his highly cited 2024 work, Thompson pioneered the use of a learned deep decoder network to account for this hysteresis in forward kinematics, enabling more accurate prediction of robot shape and position. This innovation is vital for enhancing the precision and safety of flexible surgical robots as they navigate complex anatomical structures. With over 10 citations already, his work is gaining traction among researchers seeking to bridge the gap between theoretical modeling and real-world robotic control. Thompson’s achievements mark a significant step toward reducing surgical invasiveness, positioning him as a key contributor to the next generation of medical robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2