Abstract: A computer implemented method (400) of locating a plurality of mobile device trajectories (301) relative to each other and a map (1, 1?), the mobile device trajectories (301) comprising a time series of position nodes (303) joined by edges (305), the method (400) comprising: obtaining an input pose graph (311) comprising a plurality of mobile device trajectories (301) and a plurality of first constraints (309) defining the position and orientation of nodes (303) and edges (305) of the trajectories relative to each other; performing a non-linear optimisation process on the input pose graph (311) based on the first constraints (309), to reduce a cost function associated with the first constraints (309), the non-linear optimisation process providing a modified pose graph (313); extracting one or more sub-graphs from the modified pose graph (313), and for each sub-graph, individually processing the sub-graph to map match the nodes (303) and edges (305) of the sub-graph to features defined in the map (1,1?); and g

Abstract: A computer implemented method of aligning a plurality of map segments having a local reference frame to a reference map having a global reference frame, each map segment overlapping a portion of the area represented by the reference map, the method comprising: for each map segment, independently generating one or more candidate alignments, aligning the map segment to the reference map; for each candidate alignment evaluating a cost function representing the likelihood that the candidate alignment is correct; based on the candidate alignments and associated cost functions, generating one or more candidate solutions, each candidate solution comprising a single candidate alignment for each map segment; for each candidate solution, evaluating a cost function based on at least the cost functions for each candidate alignment included in the candidate solution; and based on evaluation of the cost functions, determining alignment of the plurality of map segments.

Abstract: A computer implemented method (400) of determining a location of one or more transitions (5a-e) on a map and/or the time at which one or more transitions (5a-e) occurs, the one or more transitions (5a-e) made by a set of mobile computing devices (13a-c), from a first zone (2) to a second zone (4), the method (400) comprising: obtaining (402) trajectory data representing a plurality of trajectories (302 a, b) collected from one or more mobile computing devices (13 a-c), at least some of the trajectories (302 a, b) passing through the first zone (2) and/or the second zone (4); positioning (404) the trajectories (302 a, b) in a frame of reference defined relative to the map, wherein at least part of at least some of the trajectories (302 a, b) are positioned based on correspondence with other trajectories (302 a, b); and processing the plurality of trajectories (302 a, b) positioned in the frame of reference defined relative to the map to determine the location and/or time.

Abstract: A method 400 of automatically assigning segments of trajectories 110, 120, 130 to floors of a building 100 comprises receiving 801 data concerning a trajectory from a mobile device 152, the data comprising height data and ambient signal data; segmenting 802 the trajectory using the height data, such that a change in the height data marks an end region of a segment. A change in the height data between adjacent segments is referred to as a height link. The method further comprises calculating 803 similarity values for pairs of segments based on the ambient signal data; using the similarity values, grouping 804 the segments into a plurality of groups based on the ambient signal data; checking 805 for errors in the grouping using the height links; accepting 808a the grouping if the checking does not identify any errors, or re-running 807 the grouping if it does; and, once the grouping is accepted, assigning 809 the groups to corresponding floors.