Tatiana Pelc

University of Arizona, Tel Aviv University

Papers

Total Citations

H-Index

About

Tatiana Pelc is a pioneering researcher at the intersection of robotics, neuroscience, and adaptive behavior. Her work focuses on developing biologically-inspired control systems that enable robots to navigate and regulate their behavior in complex, real-world environments. Pelc’s major contributions include the creation of a goal-oriented robot navigation learning system that leverages a multi-scale space representation, allowing autonomous agents to efficiently plan and execute paths in large-scale settings. This work, published in 2015, has garnered 33 citations for its innovative approach to spatial cognition in robotics. In a landmark 2010 study, Pelc introduced allostatic control for robot behavior regulation, drawing direct inspiration from rodent foraging strategies. By modeling how animals maintain internal stability while interacting with their environment, she demonstrated a minimal control system that approximates these biological processes, earning 32 citations for its comparative rodent-robot framework. Her research bridges the gap between theoretical neuroscience and practical robotics, offering profound insights into how internal drives shape autonomous decision-making. Pelc’s work continues to influence fields ranging from adaptive robotics to computational ethology, making her a key figure in the development of intelligent, self-regulating machines.