Robotic Swarm Autonomy

Organization
DEVCOM Army Research Laboratory
Reference Code
ARL-R-CISD-300133
Description

About the Research

This research develops behaviors and controllers for multi-agent, heterogeneous, robotic swarms. It will enable vehicles to move, orient, and collaborate in complex missions with limited human supervision. The focus is on relatively small, man-packable ground and aerial robots. Particular interests are in highly efficient, robust, and adaptive methods that exhibit excellent properties with limited computational power, storage, and bandwidth. Opportunities exist in the
following areas:


• Robotic autonomy in mixed-initiative operations
• Collaboration of small robots in communications-limited environments
• Fusion of information from heterogeneous sensors for robot missions
• Multi-robot object tracking and recognition
• Optimization of complex algorithms for computationally frugal platforms
• Experimentation and validation methods in robotic field tests

Keywords: robotic control, swarm control, robotic vision, human-robot interaction, autonomous vehicle, mapping and localization

ARL Advisor:  Joseph Davis; Pratheek Manjunath

ARL Advisor Email: joseph.davis@westpoint.edu; pratheek.manjunath@westpoint.edu

About CISD

The Computational and Information Sciences Directorate (CISD) conducts research in a variety of disciplines relevant to achieving and implementing the so-called digital battlefield. Problems address the sensing, distribution, analysis, and display of information in the modern battle space. CISD research focuses on four major areas: communications, atmospheric modeling, battlefield visualization, and computing

About ARL-RAP

The Army Research Laboratory Research Associateship Program (ARL-RAP) is designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army. Scientists and Engineers at the CCDC Army Research Laboratory (ARL) help shape and execute the Army's program for meeting the challenge of developing technologies that will support Army forces in meeting future operational needs by pursuing scientific research and technological developments in diverse fields such as: applied mathematics, atmospheric characterization, simulation and human modeling, digital/optical signal processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking, and computational and information sciences. 

A complete application includes:

  • Curriculum Vitae or Resume
  • Three References Forms
    • An email with a link to the reference form will be available in Zintellect to the applicant upon completion of the on-line application. Please send this email to persons you have selected to complete a reference.
    • References should be from persons familiar with your educational and professional qualifications (include your thesis or dissertation advisor, if applicable)
  • Transcripts
    • Transcript verifying receipt of degree must be submitted with the application. Student/unofficial copy is acceptable

If selected by an advisor the participant will also be required to write a research proposal to submit to the ARL-RAP review panel for :

  • Research topic should relate to a specific opportunity at ARL (see Research Areas)
  • The objective of the research topic should be clear and have a defined outcome
  • Explain the direction you plan to pursue
  • Include expected period for completing the study
  • Include a brief background such as preparation and motivation for the research
  • References of published efforts may be used to improve the proposal

A link to upload the proposal will be provided to the applicant once the advisor has made their selection.

Questions about this opportunity? Please email ARLFellowship@orau.org

Eligibility Requirements
  • Degree: Any degree .
  • Discipline(s):
    • Computer, Information, and Data Sciences (16 )
    • Engineering (27 )
    • Mathematics and Statistics (10 )
    • Physics (16 )
    • Science & Engineering-related (1 )