Probabilistic Approaches to Decision-Making and Cooperative Perception Under Uncertainty in Networked Robot Systems
Event details
| Date | 03.07.2013 |
| Hour | 16:15 › 17:15 |
| Speaker |
Pedro U. Lima, Professor at the Instituto Superior Tecnico, Lisboa, Portugal |
| Location | |
| Category | Conferences - Seminars |
Bio:
Associate Professor (with "Agregação") at the Instituto Superior Técnico (IST) - Lisbon Technical University (IST/UTL)
Member of the Institute for Systems and Robotics at Lisbon (ISR/IST) (where he coordinates the Intelligent Robots and Systems group ) since 1994.
Ph.D. degree in Electrical Engineering from Rensselaer Polytechnic Institute (RPI) , Troy, NY - USA, (1994).
MSc degree from IST (1989) in Electrical and Computer Engineering.
Licenciatura degree from IST (1984) in Electrical and Computer Engineering.
Research interests: Intelligent Control Systems, applications of Discrete Event Dynamic Systems theory and Planning Under Uncertainty to the real-time control and operation of large-scale complex systems (mainly Robotics, especially multi-robot systems)
Abstract:
In robotics, sensing and effects of actions have associated uncertainty due to several factors (e.g., incomplete modeling, occlusions, sensor noise, miscalibrations). Probability theory and decision-theoretic approaches provide relevant tools to handle modeling, decision-making and perception under uncertainty for robot systems. In this talk I will introduce recent results from the group I coordinate at the Institute for Systems and Robotics at IST, Lisbon on using Bayesian inference and (partially observable) Markov decision processes to model and solve problems of cooperative perception and decision-making in real systems composed of multiple networked mobile robots and static sensors.
Associate Professor (with "Agregação") at the Instituto Superior Técnico (IST) - Lisbon Technical University (IST/UTL)
Member of the Institute for Systems and Robotics at Lisbon (ISR/IST) (where he coordinates the Intelligent Robots and Systems group ) since 1994.
Ph.D. degree in Electrical Engineering from Rensselaer Polytechnic Institute (RPI) , Troy, NY - USA, (1994).
MSc degree from IST (1989) in Electrical and Computer Engineering.
Licenciatura degree from IST (1984) in Electrical and Computer Engineering.
Research interests: Intelligent Control Systems, applications of Discrete Event Dynamic Systems theory and Planning Under Uncertainty to the real-time control and operation of large-scale complex systems (mainly Robotics, especially multi-robot systems)
Abstract:
In robotics, sensing and effects of actions have associated uncertainty due to several factors (e.g., incomplete modeling, occlusions, sensor noise, miscalibrations). Probability theory and decision-theoretic approaches provide relevant tools to handle modeling, decision-making and perception under uncertainty for robot systems. In this talk I will introduce recent results from the group I coordinate at the Institute for Systems and Robotics at IST, Lisbon on using Bayesian inference and (partially observable) Markov decision processes to model and solve problems of cooperative perception and decision-making in real systems composed of multiple networked mobile robots and static sensors.
Links
Practical information
- General public
- Free
Organizer
- Prof. Alcherio Martinoli (DISAL)
Contact
- Milos Vasic (DISAL)