USF inventors have devised a novel concept called stochastic perception or the ability for a robot to dynamically estimate the measurement model given the states of a robot and its environment. This method uses conditional probabilistic model to train itself and later predict the measurement model. This novel concept has a wide range of applications in the field of robotics, as it helps to estimate the measurement model given the states of a robot and its environment.
Robots and Landmarks Used to Collect Data Set