Realism and Effectiveness of Robotic Moving Targets

Abstract

For the vast majority of U.S. Army Soldiers, the first opportunity to engage a realistic moving target with small arms is in combat. Even Infantry Soldiers and special-skill Soldiers (e.g., snipers) have very limited opportunities to train realistic moving-target engagements. Without the opportunity to practice engaging realistic moving targets, the Soldier is not able to develop the correct perceptual and motor tuning to adequately engage live moving targets. One solution for the lack of moving target training capabilities is the use of robotic human-type targets (RHTTs). RHTTs can present a realistic three-dimensional human-sized target that can freely move with semi-autonomous control. The U.S. Army Research Institute for the Behavioral and Social Sciences was asked to assist in the assessment of the effectiveness and perceptions of this capability. Perceptions of realism, shooting performance metrics, and training capabilities inventories were collected from Soldiers training with one type of RHTT to determine effectiveness and realism. Overall, the evidence suggests that RHTTs can help improve performance on moving target tasks and RHTTs were perceived positively by Soldiers who trained with them.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2017
Accession Number
AD1039752

Entities

People

  • David R. James
  • Elizabeth R. Uhl
  • Marc Jackson
  • Martin L. Bink

Organizations

  • U.S. Army Research Institute for the Behavioral and Social Sciences

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Ammunition
  • Army
  • Army Personnel
  • Education
  • Infantry
  • Military Research
  • Moving Targets
  • Psychology
  • Small Arms
  • Social Sciences
  • Students
  • Targets
  • Three Dimensional
  • Training
  • Two Dimensional
  • Warfare
  • Weapons

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Marksmanship and Weaponry.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Autonomy
  • Autonomy - UAVs