Research Professor, Sungkyunkwan University, South Korea
Dr. Nabih Pico is an accomplished researcher and educator in the field of autonomous robot navigation and artificial intelligence. With a Ph.D. in Mechanical Engineering from Sungkyunkwan University, South Korea, he is an expert in mobile robots, robotics intelligence, and machine learning. He currently serves as a Research Professor at Sungkyunkwan University, leading cutting-edge research in robotics, and is also an Assistant Professor at ESPOL-FIEC, Ecuador. Throughout his career, Dr. Pico has made significant strides in the development of autonomous navigation systems, dynamic obstacle tracking, and deep reinforcement learning. His work has been recognized globally, earning awards such as the Grand Prize in Research from Sungkyunkwan University. He has contributed extensively to academic publications, conferences, and has filed numerous patents in the robotics domain. His research continues to push boundaries in autonomous robot navigation, improving performance in diverse and challenging environments.
Profile
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Education
Dr. Nabih Pico completed his Ph.D. in Mechanical Engineering from Sungkyunkwan University, South Korea, where he focused on autonomous robot navigation, machine learning, and deep reinforcement learning. He earned his Bachelor’s degree in Electronics and Telecommunications Engineering from Escuela Politécnica del Litoral, Ecuador, in 2014. During his Ph.D. studies, Dr. Pico specialized in robotics, working extensively on mobile robot design, dynamic obstacle recognition, and innovative solutions for autonomous navigation in outdoor and indoor environments. His research journey has helped shape the development of smarter, more adaptive robotic systems.
Experience
Dr. Nabih Pico currently holds positions as a Research Professor at Sungkyunkwan University, where he leads research in autonomous robot navigation and AI applications for robotics. He is also an Assistant Professor at ESPOL-FIEC, Ecuador, focusing on robotics and teaching remotely. Dr. Pico’s past roles include a Postdoctoral Research position at Sungkyunkwan University in collaboration with Hyundai Robotics, where he led projects on AI-driven obstacle recognition and dynamic navigation. Previously, he was a Ph.D. student at Sungkyunkwan University-KETI, where he pioneered mobile robot development capable of climbing stairs and detecting irregular terrains using LiDAR sensors. His work has included designing robots to navigate diverse environments and improving their stability and adaptability. Dr. Pico has led multiple industrial and academic projects, contributed to scientific papers, and patented innovative solutions for robotics challenges.
Awards and Honors
Dr. Nabih Pico’s academic achievements have been recognized with several prestigious awards. He received the Grand Prize in Research at the School of Mechanical Engineering, Sungkyunkwan University, for his work on enhancing the intelligence of robots for autonomous navigation in indoor environments based on Deep Reinforcement Learning. In 2024, Dr. Pico was honored with the Postdoctoral Research Award at the 2024 Graduate School Research Achievement Competition at Sungkyunkwan University. His research excellence and contributions to robotics also earned him accolades like the SKKU Human-Centered Convergence Machine Solution Future Talent Training Award. These honors highlight his profound impact on the field of robotics and his leadership in autonomous navigation research, which has advanced the development of intelligent mobile robots.
Research Focus
Dr. Nabih Pico’s research focuses on autonomous robot navigation, machine learning, and artificial intelligence applications in robotics. He specializes in deep reinforcement learning (DRL) for improving robot decision-making and autonomy in dynamic environments. His projects revolve around mobile robots designed to navigate through complex and irregular terrains, including stairs, slopes, and obstacles. Dr. Pico has developed various solutions, such as dynamic obstacle recognition and the integration of LiDAR sensors for terrain detection. He is committed to advancing the capabilities of robots for both indoor and outdoor applications, including in industrial settings where robots must adapt to challenging conditions. His research also emphasizes enhancing robot mobility through innovative suspension systems and autonomous control strategies. With a keen interest in real-time processing and multi-sensor fusion, Dr. Pico continues to explore ways AI and machine learning can improve robot performance and decision-making in diverse environments.
Publication Top Notes
- Memory-driven deep-reinforcement learning for autonomous robot navigation in partially observable environments 📄
- Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation 🛠️
- Task-Motion Planning System for Socially Viable Service Robots Based on Object Manipulation 🤖
- Unloading sequence planning for autonomous robotic container-unloading system using A-star search algorithm 🛳️
- Simultaneous Multi-channel Positive and Negative Pneumatic Boosting System for Operating Pneumatic Soft Actuators 🌬️
- Static and Dynamic Collision Avoidance for Autonomous Robot Navigation in Diverse Scenarios based on Deep Reinforcement Learning ⚙️
- Variable Admittance Control for Compliant Collaboration in Physical Human-Robot-Environment Interaction 👫
- Application of A Reliable Dynamic Friction Model for Accurate Dynamic Model Parameters Estimation of Robot Manipulators 🔧
- Box segmentation, position, and size estimation for robotic box handling applications 📦
- Climbing control of autonomous mobile robot with estimation of wheel slip and wheel-ground contact angle 🚶♂️