As part of my PhD, I created a spiking neural network capable of making directional decisions which leads a robot along paths of different shapes in a real-world environment. The robot performs fully autonomously, using only locally sourced olfactory data and no additional sensors. The SNN is in full control …

As part of my PhD research, I collected ground truth data to validate the spiking neural network (SNN) and to make adjustments when necessary. The robot was operated in teleoperation mode, controlled using a PS4 remote controller. During this process, I manually guided the robot forward, and when the sensors …

As part of my PhD, I conducted a proof-of-concept study. The purpose of the study was to assess the performance of a robot that integrated the deadband-sampling event-based processing method with the custom electronic nose (e-nose) and the one-dimensional Braitenberg-style control algorithm. Confronting live data in a real-world environment, facing …