Efficient and robust spiking neural circuit for navigation inspired by echolocating bats

Pulkit Tandon, Yash H. Malviya, Bipin Rajendran

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


We demonstrate a spiking neural circuit for azimuth angle detection inspired by the echolocation circuits of the Horseshoe bat Rhinolophus ferrumequinum and utilize it to devise a model for navigation and target tracking, capturing several key aspects of information transmission in biology. Our network, using only a simple local-information based sensor implementing the cardioid angular gain function, operates at biological spike rate of approximately 10 Hz. The network tracks large angular targets (60°) within 1 sec with a 10% RMS error. We study the navigational ability of our model for foraging and target localization tasks in a forest of obstacles and show that it requires less than 200X spike-triggered decisions, while suffering less than 1% loss in performance compared to a proportional-integral-derivative controller, in the presence of 50% additive noise. Superior performance can be obtained at a higher average spike rate of 100 Hz and 1000 Hz, but even the accelerated networks require 20X and 10X lesser decisions respectively, demonstrating the superior computational efficiency of bio-inspired information processing systems.

Original languageEnglish (US)
Pages (from-to)946-954
Number of pages9
JournalAdvances in Neural Information Processing Systems
StatePublished - 2016
Event30th Annual Conference on Neural Information Processing Systems, NIPS 2016 - Barcelona, Spain
Duration: Dec 5 2016Dec 10 2016

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing


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