AAAI Publications, Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence

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Interruptable Autonomy: Towards Dialog-Based Robot Task Management
Yichao Sun, Brian Coltin, Manuela Veloso

Last modified: 2013-06-29

Abstract


We have been successfully deploying mobile service robots in an office building to execute user-requested tasks, such as delivering messages, transporting items, escorting people, and enabling telepresence. Users submit task requests to a dedicated website which forms a schedule of tasks for the robots to execute. The robots autonomously navigate in the building to complete their tasks. However, upon observing the many successful task executions, we realized that the robots are too autonomous in their determination to execute a planned task, with no mechanism to interrupt or redirect the robot through local interaction. In this work, we analyze the challenges of this goal of interruption, and contribute an approach to interrupt the robot anywhere during its execution through spoken dialog. Tasks can then be modified or new tasks can be added through speech, allowing users to manage the robot’s schedule. We discuss the response of the robot to human interruptions. We also introduce a finite state machine based on spoken dialog to handle the conversations that might occur during task execution. The goal is for the robot to fulfill humans’ requests as much as possible while minimizing the impact to the ongoing and pending tasks. We present examples of our task interruption scheme executing on robots to demonstrate its effectiveness.

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