A Study of the Development of the Ability of the Archives Department of the Hudson's Bay Company to Carry Out Document Repairs

The objective of this thesis was to determine whether the establishment and operation of an archives services by the Hudson's Bay Company had an effect on the company's ability to carry out document repairs. Data collection methods included reviews of published material, archival records of the Hudson's Bay Company, and semi-structured interviews. The study found that the Hudson's Bay Company's commitment to operating a modern archives service in accordance with accepted archive administration practices had a substantial effect on its ability to carry out document repairs. The principled approach to repair, as practiced by the Public Record Office, was a major influence. A review of secondary sources placed this development squarely within the context of archival developments in 20th century England. Overall, the thesis findings add to the growing conversation about conservation history in England, in particular, archive conservation history as it occurred outside of the Public Record Office in the 20th century, by discussing how some methods of repair that were devised, adopted and extended by the Public Record Office in the 19th and 20th centuries were adopted and applied in the 20th century by a well-established business corporation.

Estimating the Heading of a Husky Mobile Robot with a LiDAR Compass based on Direction Maps

Without an absolute position sensor (e.g., GPS), an accurate heading estimate is necessary for proper localization of an autonomous unmanned vehicle or robot. This paper introduces direction maps (DMs), which represent the directions of only dominant surfaces of the vehicle’s environment and can be created with negligible effort. Given an environment with reoccurring surface directions (e.g., walls, buildings, parked cars), lines extracted from laser scans can be matched with a DM to provide an extremely lightweight heading estimate that is shown, through experimentation, to drastically reduce the growth of heading errors. The algorithm was tested using a Husky A200 mobile robot in a warehouse environment over traverses hundreds of metres in length. When a simple a priori DM was provided, the resulting heading estimation showed virtually no error growth.