Patricio Encalada
Papers
7
Total Citations
39
H-Index
5
About
Patricio Encalada is a robotics researcher whose work sits at the intersection of autonomous navigation, deep learning, and human-robot interaction. His primary contributions focus on enabling robots to perceive and act intelligently in human environments, with a particular emphasis on social robotics and rescue applications. Encalada has pioneered the integration of Convolutional Neural Networks (CNNs) for gesticulation control in social robots, allowing machines to interpret and respond to human gestures—a key step toward more natural human-robot collaboration. His research on the KUKA YouBot demonstrates a comprehensive approach to autonomy, combining path planning, traffic signal recognition, and object detection with deep learning networks for both navigation and human rescue scenarios. With over 39 citations across his most influential works, all published in 2018-2019, Encalada’s impact is concentrated and timely. His notable achievement lies in the successful fusion of OpenCV, Python, and ROS to create robust, deep-learning-driven control systems, as exemplified in his work on autonomous driving with the NAO robot. For students and researchers, Encalada’s portfolio offers a clear blueprint for building socially aware, autonomous robots that can navigate complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
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- 2Intelligent Autonomous Navigation of Robot KUKA YouBot6 citations · 2019
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