Universidade Federal do Rio Grande do Norte
🇧🇷 BR
Papers
167
Total Citations
2,824
H-Index
25
Researchers
197
About
The Universidade Federal do Rio Grande do Norte (UFRN) has established itself as a dynamic and multifaceted research institution with remarkable breadth across autonomous systems, mobile robotics, and applied artificial intelligence. Headquartered in Natal, Brazil, UFRN has cultivated a distinctive identity through pioneering contributions in autonomous marine vehicles, mobile robot control, and educational robotics, positioning it as one of Latin America's most productive robotics research centers. UFRN's robotics program is perhaps best recognized for its sustained excellence in unmanned surface vehicles (USVs) and autonomous maritime systems. Researchers have made landmark contributions to disaster robotics, producing a highly cited survey on USVs that has shaped the field's research agenda globally, alongside innovative work on sailboat robots employing Q-learning for intelligent path planning and realistic environmental simulation tools that accelerate development cycles. Complementing this maritime expertise is deep specialization in model predictive control (MPC) for nonholonomic mobile robots, with multiple influential publications establishing the institution as a leading authority on trajectory tracking and perception-driven stochastic control. The institution's impact extends into rehabilitation robotics, where systematic reviews on robotic-assisted gait for spinal cord injury patients have garnered significant clinical attention, and into sensor modeling, including widely adopted error characterization of stereoscopic vision systems. UFRN has also demonstrated long-standing commitment to science education through its RoboEduc and EduROSC-Kids platforms, which have brought hands-on robotics learning to underserved Brazilian communities for nearly two decades. With papers accumulating hundreds of citations across control theory, disaster response, computer vision, and natural language processing, UFRN offers prospective students and collaborators an intellectually vibrant environment where theoretical rigor meets socially impactful application.
Research Focus
Key Achievements
Top Papers
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- 7Depth Data Error Modeling of the ZED 3D Vision Sensor from Stereolabs97 citations · 2018
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- 9Unmanned Surface Vehicle Simulator with Realistic Environmental Disturbances71 citations · 2019
- 10High-Level Path Planning for an Autonomous Sailboat Robot Using Q-Learning70 citations · 2020
Faculty & Researchers
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