Carnegie Mellon University
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Towards Task-Level Planning: Action-Based Sensor Design

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journal contribution
posted on 1992-01-01, 00:00 authored by Michael Erdmann
This research proposes a method for automatically designing sensors from the specification of a robot's task, its actions, and its uncertainty in control. The sensors provide precisely the information required by the robot to perform its task, despite uncertainty in sensing and control. The key idea is to generate a strategy for a robot task by using a backchaining planner that assumes perfect sensing while taking careful account of control uncertainty. The resulting plan indirectly specifies a sensor that tells the robot when to execute which action. Although the planner assumes perfect sensing information, the sensor need not actually provide perfect information. Instead, the sensor provides only the information required for the plan to function correctly. This report is a revised version of a proposal currently submitted to NSF.


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