Decision-Theoretic Layered Robotic Control Architecture

Proceedings of the AAAI Conference on Artificial Intelligence, 16

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 16

Student Abstracts

One of the current methods for developing task control software for robots is a layering approach. This approach generally consists of a symbolic planner, a task sequencer, and a behavioral robotic controller. The task sequencer is responsible for taking a command from an abstract plan and selecting which robot level actions and behaviors to execute. This representation leads to a robust functioning software control for a robot and a single task. When the robot must be reconfigured for a new task, elements must be added to the sequencer, and behaviors to the behavioral controller. We are currently developing a decision-theoretic planner to function as the planning and sequencing layers for the architecture. It is our expectation that using a decision-theoretic planner as the sequencer will reduce the amount of work to reconfigure for a new task.