NICOP - Collective sensing and decision making in a bat swarm

Abstract

Collective sensing and decision making in a bat swarm:In applications where multiple unmanned systems must perform a task collectively, effective and efficient algorithms are needed to coordinate the swarm by utilizing the individuals limited capabilities well, and achieving an augmented collective performance. As tasks become more complex and targets become more challenging, such swarm autonomy algorithms, for both sensing and guidance, have become increasingly more important for the Navy. Several bio-inspired algorithms have been suggested by US and international institutions and some limited observations have been made on insects and animals. However, the swarming behavior of biological swarms have not been studied with comprehensive and quantitative data collection. The innovation of this proposal is that it is proposing to collect rigorous data from bat swarms indoors and outdoors, and develop an analytical model that can explain the observed data. This is an unprecedented study that is made possible by the unique know-how, and instrumentation capabilties developed at Tel Aviv University in the past five years. In the laboratory, the PI will use an advanced multi-camera tracking system to track a group of bats hunting in tight proximity with a spatial resolution of 1mm. In the field, he will use his novel miniature on-board (on-bat) sensors to track the movement and bio-SONAR activity of multiple bats as they fly and hunt over dozens of kilometers. The science of autonomy Program Officer in Code 35, Dr. Marc Steinberg expressed strong interest in this study. In addition Tom McKenna (Code 33) and Harold Hawkins (Code 34) are also interested. The CNR visited Dr. Yovel s lab in 2015 and showed significant enthusiasm for the fundamental and advanced studies conducted in this lab. ONR Code 34 will fund fully the first year of this proposal and will co-fund years 2 and 3. The desired outcomes are i) valuable data on the collective sensing and flight behavior of bat swarms in pursuit of pray, ii) an analytical model that captures the bat swarm sensing, decision, and guidance mechanisms, iii) a set of small swimming robots that implement a swarming algorithm based on the model, iv) reports and publications on findings and developments. I recommend funding this proposal.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 30, 2016
Source ID
N629091612133

Entities

People

  • Yosef Yovel

Organizations

  • Office of Naval Research
  • Tel Aviv University
  • United States Navy

Tags

Readers

  • Aerospace Engineering
  • Computer Vision.
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control