Paul Newman

TL;DR: This paper shows how by instantiating a parallel image processing stream which operates on illumination-invariant images, it can substantially improve the performance of an outdoor visual navigation system and suggests that for little cost it becomes a viable tool for those concerned with having robots operate for long periods outdoors.

TL;DR: This paper describes a probabilistic framework for appearance based navigation and mapping using spatial and visual appearance data and explicitly model the spatial distribution of visual words as a random graph in which nodes are visual words and edges are distributions over distances.

TL;DR: An approach which allows us to incrementally learn a model whose complexity varies naturally in accordance with variation of scene appearance is described, implemented and validated.

TL;DR: This article introduces a simple but novel representation of the environment in terms of a sequence of relative locations, and demonstrates precise local mapping and easy navigation using the relative map, and importantly shows that this can be done without requiring a global minimisation after loop closure.

TL;DR: An overview of the V-Charge system is presented, from the platform setup to the mapping, perception, and planning sub-systems, which is able to automate valet parking and recharging for integration into a future transportation system.