Precision Timing and Measurement for Inference with Laser and Vision

Abstract

This thesis is about precise acquisition and inference of 3D range data. The intended application domain is mobile robotics. We investigate a number of key issues in the data gathering process, showing that a careful treatment of each stage in the pipeline is vital for producing dense accurate representations. We describe a low cost 3D laser system capable of generating high quality data from a continuously moving platform. The hardware, data capture, calibration and processing techniques we have developed allow us to produce remarkably detailed point clouds. Our laser systems rapid scanning of the environment enables the correction and augmentation of the robots odometry system, by tracking planar features in consecutive sweeps of the environment. An essential part of the data acquisition pipeline is accurate timestamping of data from different sources. We describe a new and very efficient algorithm for the rapid on line synchronization of computer clocks distributed over a network. The algorithm, known as TICSync+, is capable of achieving performance measured in Parts Per Billion and deals naturally with common clock upset events. We also contribute a method for fusing point clouds with camera images to produce dense and accurate range maps of much higher resolution than the input range data. We make use of structural similarities in range and intensity data. Our use of a 2nd-Order smoothness prior allows the method to infer surfaces of arbitrary slope, as well as to reconstruct curved surfaces where appropriate.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 29, 2010
Accession Number
AD1018083

Entities

People

  • Alastair Harrison

Organizations

  • University of Oxford

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Change Detection
  • Computer Programming
  • Computer Vision
  • Computers
  • Data Acquisition
  • Data Processing
  • Detectors
  • Geometry
  • Grids
  • Information Science
  • Linear Programming
  • Operating Systems
  • Probabilistic Models
  • Simultaneous Localization And Mapping
  • Supervised Machine Learning
  • Trees (Data Structures)

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Positioning, Navigation, and Timing (PNT) Technology.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Autonomy
  • Directed Energy