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Shaping of Shared Autonomous Solutions With Minimal Interaction.

Christopher Reardon1, Hao Zhang2, Jonathan Fink1

  • 1United States Army Research Laboratory, Adelphi, MD, United States.

Frontiers in Neurorobotics
|September 21, 2018
PubMed
Summary

Interactive Shared Solution Shaping (IS3) allows humans to guide autonomous systems with minimal input. This method optimizes robot search routes, improving target detection and staying within budget constraints.

Keywords:
artificial intelligenceautonomous surveillancehuman-robot interactionroboticsshared autonomy

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • Specifying problems for autonomous systems is a key challenge in shared autonomy.
  • Existing methods often require extensive human input or complete information transfer.

Purpose of the Study:

  • To introduce and evaluate the Interactive Shared Solution Shaping (IS3) paradigm.
  • To demonstrate that minimal human interaction can optimize autonomous planning.

Main Methods:

  • Developed the IS3 framework for human-robot collaborative planning.
  • Applied IS3 to resource-constrained mobile search and surveillance tasks.
  • Conducted experiments to assess route generation and performance.

Main Results:

  • IS3-generated routes improved target detection performance and reduced variance.
  • Optimized the trade-off between performance and interaction cost.
  • Demonstrated real-world feasibility with a robot operating within budget constraints.

Conclusions:

  • IS3 enables efficient human guidance of autonomous systems.
  • Minimal interaction effectively shapes autonomous planning for complex tasks.
  • The IS3 paradigm offers a practical approach to shared autonomy in mobile robotics.