Methods and systems for geo-referencing mapping systems
A method includes receiving a trajectory dataset including a plurality of geospatial points forming a point cloud and acquired along a trajectory wherein for each of the plurality of geospatial points there is a defined an x-coordinate, a y-coordinate and a z-coordinate and at least one mapping device orientation attribute, segmenting the trajectory dataset into a plurality of segments, determining at least one relative constraint for each of the plurality of segments and utilizing, for each of the plurality of segments, at least one of the determined relative constraints to determine a relative position of at least two of the plurality of segments.
1. A method comprising:
generating a point cloud comprising both positional and pose data from a mapping system comprising a LIDAR and a retro-reflector along a first trajectory;
receiving, while generating the point cloud, data from a total station comprising a second trajectory, the received data comprising a position of the mapping system relative to a position of the total station;
adjusting the first trajectory based, at least in part, on the second trajectory; and
determining a relative timing correlation by correlating speeds of the first trajectory and the second trajectory, wherein correlating the speeds comprises maximizing a sum of one or more products by adjusting a time offset of one or more pairs of synchronized data points.
2. A method comprising:
generating a point cloud comprising both positional and pose data from a mapping system comprising a LIDAR and a retro-reflector along a first trajectory;
receiving, while generating the point cloud, data from a total station comprising a second trajectory, the received data comprising a position of the mapping system relative to a position of the total station;
adjusting the first trajectory based, at least in part, on the second trajectory; and
determining a relative timing correlation by correlating speeds of the first trajectory and the second trajectory, wherein correlating the speeds comprises maximizing an R 2 residual for a linear-least squared fitting of one or more pairs of synchronized data points.
3. A system comprising:
a mapping system comprising a LIDAR a retro-reflector and a processor encoded with instructions that when executed cause the mapping system to:
generate a point cloud comprising both positional and pose data along a first trajectory;
receive, while generating the point cloud, data from a total station comprising a second trajectory the received data comprising a position of the mapping system relative to a position of the total station;
adjust the first trajectory based, at least in part, on the second trajectory; and
determine a relative timing correlation by correlating speeds of the first trajectory and the second trajectory, wherein correlating the speeds comprises maximizing a sum of one or more products by adjusting a time offset of one or more pairs of synchronized data points.
4. A system comprising:
a mapping system comprising a LIDAR a retro-reflector and a processor encoded with instructions that when executed cause the mapping system to:
generate a point cloud comprising both positional and pose data along a first trajectory;
receive, while generating the point cloud, data from a total station comprising a second trajectory the received data comprising a position of the mapping system relative to a position of the total station;
adjust the first trajectory based, at least in part, on the second trajectory; and
determine a relative timing correlation by correlating speeds of the first trajectory and the second trajectory, wherein correlating the speeds comprises maximizing an R 2 residual for a linear-least squared fitting of one or more pairs of synchronized data points.