WHAT WE DO

Fuzzy Control

Fuzzy control is an engineering technique that uses fuzzy sets and fuzzy logic to deal with uncertainty and imprecision in control systems. In our research group, we focus on developing advanced fuzzy control algorithms to solve problems in robotics, industrial process control and autonomous vehicles, among others. We seek to improve the efficiency and accuracy of fuzzy control and explore new applications through simulations and tests in real environments, thus contributing to the advancement of this methodology in complex real-world systems.

Interactive Robots

Our research group focuses on developing interactive robots that can communicate intelligently with humans and adapt to various applications, such as home assistance, medical care and industrial collaboration. We use advanced artificial intelligence and machine learning algorithms to improve sensory perception, natural language processing and decision making, ensuring intuitive and safe interaction. We also investigate ethical and safety aspects of human-robot interaction to ensure that our robots are reliable and respectful of users and the environment.

Artificial Intelligence

Artificial intelligence is a discipline of computer science that seeks to develop systems and programs capable of emulating human intelligence, allowing them to learn, reason, perceive and make decisions autonomously. In our research group, we are at the forefront of artificial intelligence, exploring and developing innovative algorithms for machine learning, neural networks and natural language processing. We work to push the boundaries of artificial intelligence and apply it to practical solutions that improve efficiency and quality of life in various fields.

Combinatorial Optimization

We focus on combinatorial optimization, a discipline that seeks to find the best solution among a finite set of options, considering specific constraints and criteria. We work on the development of advanced algorithms, heuristics, and artificial intelligence techniques to solve complex problems in diverse areas, such as logistics, operations planning, and network design. Our goal is to apply these solutions to real-world problems, contributing to the advancement and improvement of combinatorial optimization in different industries and practical contexts.

Robot Navigation

In our research group, we are dedicated to developing and improving advanced navigation systems for robots, focusing on simultaneous localization and mapping (SLAM), path planning and obstacle perception techniques. Our goal is to create highly efficient, adaptable and safe robots that can operate in diverse environments and conditions. Through testing and validation in simulations and real environments, we seek to ensure the robustness of our solutions, while exploring new applications and challenges.

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