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Experiments in Human-Robot Teams Curtis W. Nielsen, Michael A. Goodrich, Jacob W. Crandall Brigham Young University Motivation Search and Rescue Robotics Still in its infancy Current methods have very high workload The Questions

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experiments in human robot teams

Experiments in Human-Robot Teams

Curtis W. Nielsen, Michael A. Goodrich, Jacob W. Crandall

Brigham Young University

motivation
Motivation
  • Search and Rescue Robotics
    • Still in its infancy
    • Current methods have very high workload
the questions
The Questions

How do human-robot interactions affect team performance and human workload?

Where is the “Sweet Spot?”

procedure
Procedure
  • Domain
    • Topological map-building
  • Interaction Schemes
    • Teleoperate
    • Point to Point
    • Region of Interest
  • Experiment
behavior based landmarks
Behavior-based Landmarks
  • Set of behaviors afforded to the robot
    • Affordance: “the perceived actionable properties between the world and an actor” (Gibson)
    • Actor = robot
  • Afforded behaviors: turn right, turn left, go forward
  • Afforded behaviors are found using filtered sonar measurements
building a topological map
Building a Topological Map

Classify a landmark

Disambiguate

landmarks

Choose an

action

characterizing the interaction schemes
Characterizing the interaction schemes
  • Landmark classification
  • Landmark disambiguation
  • Choose an action
  • Advantages
  • Disadvantages
teleoperate tol
Teleoperate (TOL)
  • Choose an action: Human
  • Landmark classification:Human
  • Landmark disambiguation:Human
  • Advantage: Human has very high control of the movement of the robot
  • Disadvantage: The human must devote a lot of attention to the robot
point to point ptp
Point To Point (PTP)
  • Choose an action: Human
  • Landmark classification:Robot
  • Landmark disambiguation:Human
  • Advantage: Relatively low workload
  • Disadvantage: Requires human control for each new action
region of interest roi
Region of Interest (ROI)
  • Choose an action: Human / Robot
  • Landmark classification:Robot
  • Landmark disambiguation:Robot
  • Advantage: Very little human workload
  • Disadvantage: Takes a long time to disambiguate landmarks
joystick control
Joystick Control

Landmark Disambiguation

Landmark

Classification

Action Selection

point to point control
Point to Point Control

Landmark Disambiguation

Landmark

Classification

Action Selection

region of interest control
Region of Interest Control

Landmark Disambiguation

Landmark

Recognition

Action Selection

measuring performance
Measuring Performance

The time it takes for the system to complete an accurate map of the environment.

Time…

measuring workload behavioral entropy
Measuring Workload: Behavioral Entropy
  • Entropy of the joystick (Boer)
  • Velocity of the mouse.
  • Button clicks on the mouse and joystick
  • Change robots
  • Scaling issues
results

2-PTP, TOL

ROI, PTP, TOL

2-ROI, TOL

2-PTP, ROI

3-PTP

3-ROI

2-ROI, PTP

Results

Tradeoff Curve

Without Teleop

With Teleop

conclusions
Conclusions
  • Measured performance and workload for a system where a human controls 3 robots in a map-building task.
  • Analyzed the tradeoffs in terms of workload and performance of changing interaction schemes between robots.
  • Found a sweet spot where performance is relatively high and workload is relatively low.
  • Sweet spot can change as representation and autonomy level change.
questions for future work
Questions for Future Work
  • Vary the number of robots?
  • Vary the number of users?
  • Vary environment complexity?
  • Dynamic autonomy?
  • Workload measurements (scaling issues)?