University of Pennsylvania MAGIC 2010 Final Report

Abstract

In this report, we describe the technical approach and algorithms that have been used by the Univ. of Pennsylvania in the MAGIC 2010 competition. We have constructed and deployed a multivehicle robot team, consisting of intelligent sensor and disrupter UGVs, that can survey, map, recognize, and respond to threats in a dynamic urban environment with minimal human guidance. The custom hardware systems consist of robust and complementary sensors, integrated electronics, computation, and highly capable propulsion and actuation. The mapping, navigation, and planning software is organized hierarchically, allowing autonomous decisions to be made by the robots while enabling human operators to interact with the robot team in an efficient and strategic manner. The ground control station interfaces integrate information coming from the robots as well as metadata feeds to focus the operator attention and rapidly respond to emerging threats. These systems were developed and tested by the team to complete two phases of the MAGIC 2010 challenge in a safe and timely manner.

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Document Details

Document Type
Technical Report
Publication Date
Jan 10, 2011
Accession Number
ADA535266

Entities

People

  • A. Kushleyev
  • Christopher Phillips
  • D. D. Lee
  • J. Butzke
  • Kostas Daniilidis
  • M. Likhachev
  • Mark C. Phillips
  • Vipin Kumar

Organizations

  • Moore School of Electrical Engineering

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computer Vision
  • Control Systems
  • Detectors
  • Environment
  • Ground Control Stations
  • Guidance
  • Human-Machine Interfaces
  • Image Processing
  • Inertial Measurement Units
  • Measurement
  • Metadata
  • Navigation
  • Pennsylvania
  • Simulations
  • Situational Awareness
  • Three Dimensional

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Integrated Circuit Design and Technology.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Microelectronics
  • Microelectronics - Microelectromechanical Systems