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Collaborating Authors

 Michaud, Francois


Planning for Concurrent Action Executions Under Action Duration Uncertainty Using Dynamically Generated Bayesian Networks

AAAI Conferences

An interesting class of planning domains, including planning for daily activities of Mars rovers, involves achievement of goals with time constraints and concurrent actions with probabilistic durations. Current probabilistic approaches, which rely on a discrete time model, introduce a blow up in the search state-space when the two factors of action concurrency and action duration uncertainty are combined. Simulation-based and sampling probabilistic planning approaches would cope with this state explosion by avoiding storing all the explored states in memory, but they remain approximate solution approaches. In this paper, we present an alternative approach relying on a continuous time model which avoids the state explosion caused by time stamping in the presence of action concurrency and action duration uncertainty. Time is represented as a continuous random variable. The dependency between state time variables is conveyed by a Bayesian network, which is dynamically generated by a state-based forward-chaining search based on the action descriptions. A generated plan is characterized by a probability of satisfying a goal. The evaluation of this probability is done by making a query the Bayesian network.


The Robot Host Competition at the AAAI-2002 Mobile Robot Competition

AI Magazine

Robots in the Robot Host competition, part of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002) Mobile Robot Competition faced two challenges: (1) a serving task that was similar to the Hors d'Oeuvres, Anyone? Both tasks required moving carefully among people, politely offering them information or hors d'oeuvres, recognizing when the people are making a request, and answering the request.


The Robot Host Competition at the AAAI-2002 Mobile Robot Competition

AI Magazine

The entry from Kansas State University used minimal hardware sensors but used a conversation utility with a limited database to engage in conversation with users. Both tasks required moving carefully among The entry from Kansas State University (figure people, politely offering them information or 1) was developed by three exchange students hors d'oeuvres, recognizing when the people from the Czech Republic. Their entry consisted are making a request, and answering the request. of a The robot had sonar Celebrating the sixth year for the Robot Host sensors to provide obstacle avoidance and an competition, a new task, the robot information infrared sensor to sense the presence of people kiosk, was added. Three entries took on the by their temperature. Navigation was random challenge of creating host robots who can both and limited by xy bounds.


The Hors d'Oeuvres Event at the AAAI-2001 Mobile Robot Competition

AI Magazine

Serving hors d'oeuvres is not as easy as it might seem! You have to move carefully between people, gently and politely offer them hors d'oeuvres, make sure that you have not forgotten to serve someone in the room, and refill the serving tray when required. These are the challenges that robots have to face in the Hors d'Oeuvres, Anyone?


The Hors d'Oeuvres Event at the AAAI-2001 Mobile Robot Competition

AI Magazine

Serving hors d'oeuvres is not as easy as it might For the fifth five entries took on the challenge of devices were connected to both robots. Mannequins creating service robots who can offer hors were mounted on top of each robot to d'oeuvres to attendees of the robot exhibition. The robots communicated area, find and stop at people to offer food and with each other through a local area network interact with them, detect when more food is on wireless network cards on their laptop computers. For example, Ron Nucci from expected responses. The robot had voice-recognition guest, and serves him/her.