Flexible Path Planning and Navigation in Humans, Rats, and Robots

Dr. Jeffrey L. Krichmar

University of California, Irvine

Friday, October 8, 2021

11 AM – 12 PM CST

https://utsa.zoom.us/j/98953233499

Flexible path planning is necessary for reaching goals and adapting when conditions change. We introduce a biologically plausible path planning model that learns its environment, rapidly adapts to change, and plans efficient routes to goals. Because the algorithm is suitable for spike-based neuromorphic hardware, it has the potential of realizing orders of magnitude gains in power efficiency and computational gains through parallelization. In the first part of the talk, I will introduce the algorithm and show its effectiveness in autonomous robot navigation. In the second part of the talk, I will explore how this biologically inspired path planning algorithm can explain navigation strategies in humans and in rodents. I suggest that mental effort may be the reason we observe variability in human navigation. I also show that the model activity resembles neural correlates of hippocampal preplay and vicarious trial and error (VTE) observed when rodents are navigating mazes. This variation and flexibility may be beneficial for autonomous agents during information gathering and for robotic swarms.