Reproducing Fear Conditioning of Rats with Unmanned Ground Vehicles and Neuromorphic Systems

Noah Zins and Hongyu An
Michigan Technological University


Associative memory is a self-learning paradigm prevalently existing in animals enabling them to memorize the cause-and-effect relationship of concurrent events. Thus, neuromorphic systems with associative memory potentially can learn through constant interaction with surrounding environments rather than labeled datasets. In this work, we reproduce the classic fear conditioning of rats, which is a type of associative memory, using unmanned ground vehicles (UGVs), neuromorphic systems, and Hebbian learning. The UGV autonomously memorizes the cause-and-effect of the light stimulus and vibration stimulus, then conducts a movement response. The work investigates a way of a biologically plausible method enabling UGV independent learning by exploring a dynamic and unpredictable scenario.