Dr LUIS FIGUEREDO
| Biography | Luis F.C. Figueredo received his B.Sc. and M.Sc. degrees in Mechatronics and Electrical Engineering from the University of Brasilia, Brazil,. He earned his Ph.D. degree in Robotics from the same institution with an biennial award for best PhD thesis. During his thesis, he also worked at CSAIL - MIT where he received multiple awards for robot demonstrations at venues such as IROS and ICAPS. He received the prestigious Marie Skłodowska-Curie Individual Fellowship, in 2018, for his work on biomechanics-aware human-robot interaction with AI tools acknowledged on the EU Innovation Radar. He is currently an Assistant Professor at the University of Nottingham, United Kingdom, and an Associated Fellow at the Munich Inst. of Robotics and Machine Intellig. at the Tech. University of Munich. |
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| Research Interests | My vision of robotics is an all inclusive one. Particularly, human-robot collaboration requires a comprehensive view of the robot and the human capabilities. A perfect task planner that comprehends and integrates different human factors is useless if the robot is not able to satisfy its own constraints, or execute the task. At the same time, executing a task blindly, ignoring human safety, comfort and preferences may lead to poor interaction a lack of desire from the human side, which kills the purpose of the HRC. My research takes a bottom up approach, providing first real-time collision-free (when possible) planners and controllers that optimizes for safety and performance, satisfying geometric and force constraints whilst ensuring general task and constraint understanding and satisfaction. Considering human-safety in all levels of actions, and the capability of using multiple arms and to be able to plan more complex, sequential and parallel tasks. Finally, taking all those aspects into account, we can plan integrate human implicit and explicit communication, preferences and comfort. My research topics include: Manipulation planning and control; Control theory; Safety / Constraint Satisfaction in manipulation; Geometric methods; Learning by demonstration; Task definition; User-guided motion planning; Human Safety in terms of Pre-Collision Optimization; Human Safety in terms of Post-Collision Reflexes; Multi-arm Manipulation; Dual-arm manipulation; Physical human-robot interaction; Physical human-robot collaboration; Human Factors for Manipulation; Biomechanics-aware Manipulation; Ergonomics and manipulability; Natural Language processing for Manipulation; Rehabilitation Robotics; Service Robotics; Intelligent Manufacturing; |
| Scopus Author ID | 57217856344 |