Mapping

//Mapping

Building, Curating, and Querying Large-scale Data Repositories for Field Robotics Applications

Abstract—Field robotics applications have some unique and unusual data requirements -- the curating, organisation and management of which are often overlooked. An emerging theme is the use of large corpora of spatiotemporally indexed sensor data which must be searched and leveraged both offline and online. Increasingly we build systems that must never stop learning. Every [...]

Accelerating FAB-MAP with Concentration Inequalities

Abstract—We outline an approach for using concentration inequalities to perform rapid approximate multi-hypothesis testing. In a scenario where multiple hypotheses are ranked according to a large set of features, our scheme improves the efficiency of selecting the best hypothesis by providing a “bail-out threshold” at which unpromising hypotheses can be excluded from further evaluation. We [...]

Adaptive compression for 3D laser data

Abstract - This paper concerns the creation of efficient surface representations from laser point clouds created by a push broom laser system. We produce a continuous, implicit, non-parametric and non-stationary representation with an update time that is constant. This allows us to form predictions of the underlying workspace surfaces at arbitrary locations and densities. The algorithm [...]

Efficient Non-Parametric Surface Representations Using Active Sampling for Push Broom Laser Data

Abstract—This paper concerns the creation of efficient surface representations from laser point clouds. We produce a continuous, implicit, non-parametric representation with an update time that is constant. The algorithm places no restriction on the complexity of the underlying workspace surfaces and automatically prunes redundant data via an information theoretic criterion. This criterion makes the use [...]

FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance

  Abstract— This paper describes a probabilistic framework for appearance based navigation and mapping using spatial and visual appearance data. Like much recent work on appearance based navigation we adopt a bag-of-words approach in which positive or negative observations of visual words in a scene are used to discriminate between already visited and new places. [...]

Generating Implicit Surfaces from Lidar Data

Abstract—This paper is concerned with generating a continuous implicit representation of a robot’s workspace using sparse point cloud data. We adopt a Gaussian Process (GP) framework to model the underlying workspace surfaces and suggest a non- parametric formulation which allows us to capture the non-functional relation between ground plane and elevation that is not possible [...]

FAB-MAP 3D: Topological Mapping with Spatial and Visual Appearance

Abstract— This paper describes a probabilistic framework for appearance based navigation and mapping using spatial and visual appearance data. Like much recent work on appearance based navigation we adopt a bag-of-words approach in which positive or negative observations of visual words in a scene are used to discriminate between already visited and new places. In [...]

Semantic Mapping

Autonomous vehicles operating in places like parking lots can leverage of a higher-level understanding of the objects around it. For instance, the knowledge hat there is an upcoming zebra crossing should be taken into account in the vehicle’s current motion plan and speed. Also labelling of parking spots, could be crucial in other  tasks as efficient assignment of [...]