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AIC Seminar Series

Model-based Programming of Robust Agile Systems

Brian C. WilliamsMassachusetts Institute of Technology[Home Page]

Notice:  hosted by Neil Yorke-Smith

Date:  2006-10-26 at 16:00

Location:  EJ228  (Directions)

   Abstract

Autonomous, self-repairing explorers, such as deep space probes, have successfully performed complex missions by employing model-based executives that continuously monitor mission goals, diagnose failures and plan repairs. These executives employ models encoded as probabilistic constraint automata, in order to observe and control the hidden states of the system. These executives have also been incorporated within model-based programming languages that facilitate the creation of a wide range of fault adaptive systems, including automobiles and naval ships. Future explorers, such as autonomous air vehicles and walking robots, will require far greater agility, in order to robustly achieve their missions. For example, to avoid falling, a walking robot must quickly detect a loss of balance, and replan its control trajectory appropriately. This talk presents recent advances in model-based programming and execution for agile systems. First, to reason about a system’s dynamics, these executives employ probabilistic constraint automata that are extended to hybrid discrete/continuous constraints. Second, to robustly achieve missions, these executives employ planning methods that reason about continuous, as well as discrete, state changes, and employ compilation and model-predictive control methods in order to adapt on the fly. Finally, these executives employ estimation methods for hybrid PHA that detect subtle failures through active control. Model-based execution is demonstrated both on a team of cooperative air vehicles and a biped walking machine.

   Bio for Brian C. Williams

Brian Williams leads the Model-based Embedded and Robotic Systems Group at MIT, which is affiliated with the Computer Science and Artificial Intelligence Laboratory. Prof. Williams’ research concentrates on model-based autonomy – the creation of long-lived autonomous systems that are able to explore, command, diagnose and repair themselves using fast, commonsense reasoning. Current research focuses on model-based programming and cooperative robotics: Model-based programming is embedding commonsense within robotic explorers and everyday devices by incorporating model-based deductive capabilities within traditional embedded programming languages. Cooperative robotics extends model-based autonomy to robotic networks of cooperating space, air and land vehicles, on Earth or other planets. Applications include deep space explorers, distributed satellites, unmanned air vehicles, Mars rovers, intelligent offices and automobiles. Research interests include reasoning at reactive time scales, cooperative and space robotics, intelligent embedded systems, model-based programming, model-based reactive planning, execution and diagnosis, data-driven exploratory modeling, and hybrid system control.

Brian Williams received his S.B., S.M and Ph.D. from MIT in Computer Science and Electrical Engineering in 1989. He pioneered multiple fault, model-based diagnosis in the 80’s through the GDE and Sherlock systems at the Xerox Palo Alto Research Center, and model-based autonomy in the 90’s through the Livingstone model-based health management and the Burton model-based execution systems. At the NASA Ames Research Center from 1994 to 99 he formed the Autonomous Systems Area, and co-invented the Remote Agent model-based autonomous control system, which received a NASA Space Act Award in 1999. He was a member of the NASA Deep Space One probe flight team, which used remote agent to create the first fully autonomous, self-repairing explorer, demonstrated in flight in 1999. He has won two best paper prizes for his research in qualitative algebras and fast propositional inference. He was a member of the Tom Young Blue Ribbon Team in 2000, assessing future Mars missions in light of the Mars Climate Orbiter and Polar Lander incidents. He has served as guest editor of the Artificial Intelligence Journal and has been on the editorial boards of the Journal of Artificial Intelligence Research, and MIT Press. He is currently a member of the Advisory Council of the NASA Jet Propulsion Laboratory at Caltech.

Brian Williams is group lead of the Model-based Embedded and Robotic Systems group at the Massachusetts Institute of Technology, which is affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Autonomous Systems Laboratory (ASL) of the Department of Aeronautics and Astronautics.

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