Papers
7
Total Citations
41
H-Index
4
About
Orivaldo Santana is a researcher dedicated to democratizing robotics education and advancing intelligent robotic control systems. His primary research areas span educational robotics, teacher training methodologies, and machine learning applications for autonomous systems. Santana’s most significant contributions lie in developing accessible frameworks for K-12 robotics education, notably through the EduRoSC-Prof method and URA workshops, which provide structured teacher training for Brazilian public schools. His work on the low-cost, open-source URA 4.0 modular robot kit has made robotics education more attainable, while his technical innovations include the SOM-STG algorithm for legged robot locomotion control and self-learning approaches for robotic arm inverse kinematics using Kohonen maps. With over 40 citations across his most-cited works, Santana has demonstrated impact in both pedagogical and technical domains. His participation in the IEEE Open Challenge, where he developed an unsupervised machine learning algorithm for visual target identification, showcases his ability to bridge theory and practical competition. Through the MecaTeam framework for RoboCup simulation, he has also contributed to multi-agent systems. Santana’s work uniquely combines educational accessibility with technical rigor, making him a notable figure in robotics education and autonomous systems research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Analysis of Teacher Training in Educational Robotics with URA Workshops8 citations · 2020
- 3
- 4Self-learning in the inverse kinematics of robotic arm6 citations · 2017
- 5
- 6URA 4.0: A Low-Cost Modular Robot for Education2 citations · 2018
- 7