معرفی
Luís Henrique Ramilo Mota is an Assistant Professor in the Department of Information Science and Technology (ISTA) at ISCTE – Instituto Universitário de Lisboa. His research lies at the intersection of robotics, multi-agent systems, and artificial intelligence, with a strong focus on cooperative robotics and robotic soccer applications.
His primary research interests include:
- Multi-Robot Coordination
- Setplays-based Planning
- Ontology Engineering for Agent Systems
- Semantic Web Technologies
- RoboCup Simulation and Mixed Reality
- Distributed Autonomous Systems
Mota’s recent scholarly work centers on developing flexible coordination mechanisms for robotic teams, particularly through the Setplays framework, enabling robust and dynamic behavior in competitive environments like RoboCup. His publications span high-impact journals such as Data and Knowledge Engineering and Mechatronics, as well as top-tier conferences including AAMAS and IEEE RAM. His research integrates software architecture, communication protocols, and AI planning to solve real-world coordination challenges in autonomous systems.
Scientific Contributions:
- Developed the Setplay framework for multi-robot coordination
- Contributed to ontology modeling for multi-agent systems (O3F)
- Authored multiple RoboCup team description papers for FC Portugal
- Pioneered work on open, fault-tolerant robotic architectures
Advising and Collaborative Research:
While no formal students are listed, Mota has collaborated extensively with researchers such as Luís Paulo Reis, Nuno Lau, and Fernando Almeida on robotic soccer and semantic web projects. His work often involves team-based research initiatives, particularly within the RoboCup community, where he contributes to both simulation and physical visualization leagues.
Laboratories and Research Teams:
Mota is actively involved with the FC Portugal RoboCup team, contributing to both the 2D simulation and mixed reality competitions. His work supports the development of cooperative strategies and communication frameworks in multi-agent robotic systems.
