Jose Arnaldo Mascagni de Holanda
Papers
2
Total Citations
38
H-Index
2
About
Jose Arnaldo Mascagni de Holanda is a researcher whose work sits at the intersection of embedded systems, robotics, and computer vision, with a particular focus on hardware acceleration using FPGAs. His most influential contribution is an FPGA-based implementation of the Kalman filter for mobile robotics, which addresses the computationally intensive problem of simultaneous localization and mapping (SLAM). This work, which has garnered 33 citations, demonstrates how probabilistic theory can be efficiently realized in hardware to manage uncertainty in robot perception and action—a key challenge in autonomous navigation. More recently, de Holanda has explored multi-softcore FPGA architectures for accelerating the Histogram of Oriented Gradients (HOG) algorithm, a demanding task in real-time object detection. This approach, detailed in his 2016 paper, aims to balance the flexibility of software with the performance of hardware, enabling smarter embedded systems. His research is notable for bridging theoretical probabilistic methods with practical, real-time hardware solutions, making him a valuable contributor to the fields of reconfigurable computing and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Towards a multi-softcore FPGA approach for the HOG algorithm5 citations · 2016