Dr. Nicolás Navarro-Guerrero


Nicolás Navarro-Guerrero is a Research and Teaching Associate at the Department of Computer Science at the University of Hamburg, Germany. He received a Bachelor of Science on Electronic Engineering degree, and an Electronic Engineering degree both from the Universidad Técnica Federico Santa María (Valparaíso, Chile). Later, he completed his Ph.D. on Computer Science at the University of Hamburg (Germany). His Ph.D. research concerned computational models for adaptive robot behaviour based on neural mechanisms of self-preservation. It was conducted under the supervision of Prof. Dr. Stefan Wermter at the Knowledge Technology group at the University of Hamburg, Germany. His research interests include humanoid and service robots, bio-inspired sensors and signal processing, and powered rehabilitation and care equipment.

Neurocomputational Mechanisms for Adaptive Self-Preservative Robot Behaviour

October 27, -

Self-preservative mechanisms belong to the most important and essential capabilities of any organism. Mechanisms such as those involved in homeostatic, defensive, and sexual behaviours are fundamental to ensure individual survival and the perpetuation of the species. However, a simple mapping between stimuli and reactions is not enough to guarantee self-preservation in an ever-changing environment. Consequently, adaptability becomes an essential component for survival. Survival needs and their regulatory processes – although specific to current pressing needs – have system-wide implications, and they impose ground rules for more complex and motivated behaviours. For instance, they modify pain thresholds, shift attentional effort, drive motivation and elicit goal-directed behaviours, thereby establishing the basis for cognitive processes such as planning, decision making, mood and emotions. Focusing particularly on aspects of damage prevention, in this talk I will present my research on neurocomputational self-preservative mechanisms to demonstrate the potential and feasibility of including bio-inspired adaptive self-preservative mechanisms as part of real-world robotic systems.