Event-based control of autonomous agents in dynamic environments

This paper presents an approach of event-based control for the modeling of autonomous agents in a dynamic virtual environment. It constructs a biologically inspired neural network for real-time planning of collision-free paths. In addition, it uses a state-to-reference transformation to convert the stimuli of autonomous agents from the time domain to an event domain that corresponds to the perceptual inputs of agents. This event-based approach of control allows autonomous agents to move smoothly towards their goals and to make prompt reaction when environment changes take place.