Perceiving the motion of a target is essential for a successful interaction with a dynamic environment, in which objects and the robot itself move simultaneously. Event-cameras allow to track fast-moving targets, without losing information “between frames,” as a moving object triggers events from all pixels along its spatio-temporal trajectory.

We develop tracking algorithms robust to event-clutter due to ego-motion and prediction algorithms that anticipate the trajectory of the target and give sufficient decisional time to the robot to perform an adequate action. We explore data representations, algorithms and coding that guarantee real-time and low-latency processing.