Jean-Philippe Diguet
Papers
2
Total Citations
22
H-Index
2
About
Jean-Philippe Diguet is a leading researcher at the intersection of reconfigurable computing, embedded systems, and robotics. His work focuses on enabling high-performance, energy-efficient computing for autonomous systems, particularly through the use of dynamically and partially reconfigurable FPGAs. A key contribution is his pioneering application of hardware-in-the-loop simulation with dynamic partial FPGA reconfiguration for computer vision in ROS-based UAVs (2020, 15 citations), a method that accelerates safe embedded system development. In multi-robot systems, Diguet has advanced distributed intelligence by comparing market-based and deep reinforcement learning (DQN) approaches for multi-robot processing task allocation (MRpTA, 2020, 7 citations), addressing how robots collaboratively handle complex, dynamic computing tasks. His work bridges hardware acceleration and autonomous decision-making, with impact demonstrated through citations in both FPGA design and robotics communities. Diguet’s research is notable for its practical integration of reconfigurable hardware into real-world robotic platforms, making him a key figure in the evolution of adaptive, resource-constrained autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2