Hilbert maps: scalable continuous occupancy mapping with stochastic gradient descent

The vast amount of data robots can capture today motivates the development of fast and scalable statistical tools to model the environment the robot operates in. We devise a new technique for environment representation through continuous occupancy mapping that improves on the popular occupancy grip maps in two fundamental aspects: 1) it does not assume an a priori discretisation of the world into grid cells and therefore can provide maps at an...