Pablo Krupa
Papers
1
Total Citations
4
H-Index
1
About
Pablo Krupa is a researcher whose work bridges the gap between advanced control theory and practical embedded systems. His primary research areas include model predictive control (MPC), real-time control implementation, and the application of these techniques to robotic systems. Krupa’s most notable contribution is the real-time implementation of an MPC for tracking formulation, demonstrated on a two-wheeled inverted pendulum robot. This work is significant because it overcomes the computational challenges of deploying sophisticated MPC algorithms on embedded hardware, offering advantages like improved stability and constraint handling over standard formulations, all while adding only a minimal computational burden. His 2022 paper on this topic has garnered 4 citations, reflecting its relevance to researchers and engineers working on agile robotics and autonomous systems. By proving that advanced control strategies can be executed in real-time on resource-constrained platforms, Krupa is helping to enable more responsive and intelligent robots, from self-balancing transporters to drone systems, making his contributions both theoretically sound and practically impactful.
Research Focus
Key Achievements
Top Papers
- 1