Autonomy Mode Suggestions for Improving Human-Robot Interaction Michael Baker Holly A. Yanco University of Massachusetts Lowell.

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Presentation transcript:

Autonomy Mode Suggestions for Improving Human-Robot Interaction Michael Baker Holly A. Yanco University of Massachusetts Lowell

Robot-assisted Urban Search and Rescue Too dangerous for human and animal rescuers Need to locate victims who may be trapped or injured Need to navigate the robot quickly, but safely to avoid a secondary collapse – Need robot autonomy

HRI in USAR Observations Users spend too much time trying to gain situation awareness Users do not use robot autonomy modes effectively Users focus on the video feed to the exclusion of other sensor information

How Suggestions Can Help Alert the user to important opportunities, events and information – Promote user efficiency Teach the user about the robot’s autonomy modes – Alleviate confusion about robot autonomy Teach the user about the system’s capabilities and features

How Suggestions Can Help “Training wheels” for the novice user Refresher course for the experienced user Shortens training time, which may be unavailable when disaster strikes – Less to learn and remember about the interface In spite of training, users miss “obvious” sensor cues and mode switching opportunities

How a Suggestion is Made A visual cue on the interface tells the user: – That something is being suggested – What is being suggested – How to accept (take) the suggestion Intentional use of color, position, distinctive graphics and text to minimize the user’s cognitive effort

How a Suggestion is Taken The user presses a specified key Suggestion outcomes: – Switch the autonomy mode – Change the camera view or position – Turn the light on or off Ignored suggestions time out and disappear Changing conditions could cause a suggestion to disappear

Autonomy Mode Suggestions Mutual Exclusivity – One mode suggestion at a time Arbitration – The system chooses the best mode suggestion when multiple are possible Preemption – The system can preempt a mode suggestion with a better mode suggestion

Implemented Suggestions Teleoperation Mode  Safe Mode Escape Mode Center camera Change camera view Battery low Toggle light

Teleoperation -> Safe Mode Suggestion

Escape Mode Suggestion

Center Camera Suggestion

Toggle Camera Suggestion

Battery Suggestion

Toggle Light Suggestion

Toward Automatic Suggestions Use machine learning to customize suggestions for a particular user – Take suggestions automatically – Disable suggestions – Adjustable frequency and duration Smarter suggestions

Acknowledgment Thank you to Doug Few and David Bruemmer of INEEL for sharing their robot autonomy modes with us