Papers
5
Total Citations
29
H-Index
3
About
Diego S. Pereira is a robotics researcher whose work centers on safe and efficient path planning for autonomous systems, with a particular focus on the innovative Probabilistic Foam Method (PFM). His major contributions include developing and refining PFM, a planner that guarantees safe paths by propagating a structure of "bubbles" through free space, ensuring collision-free navigation. Pereira has applied this method to critical domains, such as lower limb active orthoses for obstacle overcoming, and extended it to multi-robot systems, addressing the challenge of coordinated, safe movement in static environments. His most cited work, "Safe Path Planning Based on Probabilistic Foam for a Lower Limb Active Orthosis to Overcoming an Obstacle" (2018, 9 citations), demonstrates the practical impact of his approach in assistive robotics. Additionally, his goal-biased variation of PFM (2018, 8 citations) improves efficiency by directing the search toward the target. With a total of 29 citations across his top five papers, Pereira's research is establishing a foundation for reliable robot navigation, promising safer interactions between autonomous systems and humans.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Goal-biased probabilistic foam method for robot path planning8 citations · 2018
- 4A Cloud Robotics Architecture Clone Based for a Cellbots Team2 citations · 2017
- 5A Multi-Robot Path Planning Approach Based on Probabilistic Foam2 citations · 2019