Alastair Harrison

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In this paper we describe a body of work aimed at extending the reach of mobile navigation and mapping. We describe how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full sixdegree-of-freedom outdoor navigation system. It is capable of proThe International Journal of(More)
This paper describes a method for the automatic self-calibration of a 3D Laser sensor. We wish to acquire crisp point clouds and so we adopt a measure of crispness to capture point cloud quality. We then pose the calibration problem as the task of maximising point cloud quality. Concretely, we use Rényi Quadratic Entropy to measure the degree of(More)
This paper describes an end-to-end system capable of generating high-quality 3D point clouds from the popular LMS200 laser on a continuously moving platform. We describe the hardware, data capture, calibration and data stream processing we have developed which yields remarkable detail in the generated point clouds of urban scenes. Given the increasing(More)
This paper describes a body of work aimed at extending the reach of mobile navigation and mapping. We describe how running topological and metric mapping and pose estimation processes concurrently, using vision and laser ranging, has produced a full six-degree-of-freedom outdoor navigation system. It is capable of producing intricate 3D maps over many(More)
This paper describes the design, build, automatic self-calibration and evaluation of a 3D Laser sensor using conventional parts. Our goal is to design a system, which is an order of magnitude cheaper than commercial systems, with commensurate performance. In this paper we adopt point cloud “crispness” as the measure of system performance that we wish to(More)
This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric(More)
We consider the task of processing 3D laser data for use in the Simultaneous Localization and Mapping Problem. The motivation for using 3D data comes in part from the impracticality of relying on 2D laser scanners when the vehicle operates on undulating terrain and in part from a desire to produce 3D maps of arbitrary, a priori unknown environments. We use(More)
Modern robotic systems are composed of many distributed processes sharing a common communications infrastructure. High bandwidth sensor data is often collected on one computer and served to many consumers. It is vital that every device on the network agrees on how time is measured. If not, sensor data may be at best inconsistent and at worst useless.(More)
This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric(More)
We examine why a probabilistic approach to modelling the various components of spatial language is the most practical for spatial algorithms in which they can be employed, and examine such models for prepositions such as `between' and `by'. We provide an example of such a probabilistic treatment by exploring a novel application of spatial models to the(More)