Rosiery Maia
Papers
3
Total Citations
19
H-Index
2
About
Rosiery Maia is a roboticist whose work bridges the gap between autonomous perception and collaborative multirobot learning. Her research primarily focuses on robotic mapping, multirobot cooperation, and the application of cognitive development theories to artificial systems. In her most cited work, "3D Probabilistic Occupancy Grid to Robotic Mapping with Stereo Vision" (2012, 11 citations), Maia advanced the fundamental challenge of environment mapping by developing a probabilistic framework that enables mobile robots to build accurate spatial models from stereo vision data—a critical step toward full autonomy. She further innovated in multirobot systems with her "N-learning" approach (2019, 6 citations), which introduces a practical method for teaching and acquiring behaviors across robot teams through real-time interaction, effectively allowing robots to self-program. Demonstrating a unique interdisciplinary perspective, Maia also proposed formal rules for robotic cooperation inspired by the social learning theories of Vygotsky and Piaget (2015, 2 citations), translating human developmental psychology into operational principles for robot teams. Her work is notable for its creative synthesis of engineering and cognitive science, offering novel pathways for designing more adaptive and socially-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 13D Probabilistic Occupancy Grid to Robotic Mapping with Stereo Vision11 citations · 2012
- 2
- 3Rules for Robotic Cooperation Based on Vygotsky and Piaget2 citations · 2015