Google cartography download

These can conveniently be drawn by placing the member 9 on the globe and locating each pair of corresponding points along any great circle, then tracing the great circle onto the member 9. To construct the three-way grid on the spherical triangle, the sides of the triangle are similarly divided into any desired number of parts twelve, as shown and the great circle arcs are scribed as shown in Fig.

In each case, the great circle arcs can be drawn by tracing from a globe as previously described. We now have on the member 9 a two-Way great circle grid indicated generally at 34 Fig.

It will be understood, of course, that the provision of both the rectangular and triangular grids on the one cartographic device 9 is largely a matter of convenience, and I contemplate that if desired, the triangular grid could be placed upon a separate device apart from the rectangular grid; also, that they could be located in different positions on the hemispherical member 9.

Furthermore, it is not necessary that the rectangular and triangular grids be conjoined in the manner shown in Figs. Translation from the spherical to the plane surface The fiat sections or tiles shown in Figs. Each tile is provided with a great circle grid, those on the square tiles corresponding to the spherical grid 94 and those on the triangular tiles corresponding to the grid 95 previously described.

The grids are constructed as before by dividing the sides into the desired number of equal parts. Assuming 5 intervals, we will divide into twelve parts to gain correspondence with the spherical grids. In this case, the points along the edges of the tiles are joined by straight lines. These straight lines are true representations of a projection of a great circle since the projection of a great circle is a straight line.

All of the edges of each tile are projections of great circles. Having the device of Figs. For example, let us suppose that we are mapping on one ofthe square tiles. We will place the member 9 on the globe with the spherical grid 34 overlying'that portion of the earths surface which isto be translated to the tile Fig, 6. If it is desired to have the poles at the centers of the square tiles as in the'ca'se of the map represented by Fig. The coordinates of the particular city, coast-line point, or other cartographic feature are read on the grid 34 and plotted on the grid of the tile Thus, ifthe particular'point being plotted lies at the point 3'!

This process is repeated for each point that is being translated from the spherical to the plane surface. It will, of course, be understood that the grids may be subdivided as finely as may be desired.

That is, the grid may be carried down to 1 intervals or to fractions of a degree, depending upon the accuracy desired. The same procedure is followed in translating from the globe to the triangular tile First, the member 9 is so located 'on the globe that the corners 25 and 26 of the triangular grid 35 overlie the desired points, that is, they will overlie the same points as did the corners 25 and 26 of the rectangular grid 34 during use of the latter.

Coordinates are read on the grid 35 and plotted on the grid of the tile It is not necessary that the poles be located at the centers of square tiles, and in Fig. It will be observed that in this embodiment, the land areas have been joined without sinuses.

The embodiment illustrated in Fig. A distinguishing feature of the maps of both Figs. This is possible because the sections match along edges which are representations of projected great circles. This means that distances measured along the edges of any section are true to scale, and that scale is uniform throughout. Moreover, by reason of employment of the particular method of translating from the spherical to the plane surface which I described, subsidence errors are distributed interiorly of the periphery.

This is accomplished by plotting on the great circle grid and no corrections are required. The tiles may be arranged in any manner which may be desired for the study of particular land or water features,.

With three tiles arranged as shown in Fig. If we shift the upper and lower triangular tiles into the position shown in Fig. With reference to Fig. If desired, the map maybe employed without adding the superimposed meridians and parallels.

Where the meridians and parallels are used, the great circle grid may, if desired, be removed either before or after the map has been plotted. In this case the great circle grid will have been used purely as a construction device. When the great circle grid is employed merely as a construction device for translating meridians and parallels to a plane surface, it may be desirable to plot these down to single degrees, or even to fractions of a degree.

The map itself may then be plotted directly on the coordinates of latitude and longitude, with the result of reducing the map to imaginary great circle grids, and producing a map which possesses the various advantages I have described. This system makes it possible to construct my novel map with the use of available cartographic data based on the system of latitudes and longitudes.

Among the advantages of my invention may be cited the provision of uniform scale along the periphery of all of the sections, the provision of a sectional map which can be assembled in a manner which eliminates land sinuses, and the fact that by having uniform peripheral scale with subsidence errors distributed interiorly of the periphery by plotting on a great circle grid, distortion is less than with any form of projection heretofore known.

With gnomonic projection, the scale is true only at the exact center of a section, and subsidence errors build up in a radially outward direction at an alarming rate. Some systems of cartography resort to correction of areas on what is known as the equal area basis, which only serves to enormously distort shapes. Careful study of maps constructed in accordance with my invention will show that it gives a truer overall picture of areas, boundaries, directions and distances than is attainable with any type of plane surface map heretofore known.

The terms and expressions which I have employed are used in a descriptive and not a limiting sense, and I have no intention of excluding such equivalents of the invention described, or of portions thereof, as fall within the purview of the claims.

A projected map comprising a plurality of square and triangular sections bearing respectively different map outlines and matching along edges which are representations of projected great circles with uniform scale cartographic delineation along said edges. A map comprising two or more sets of different matching map sections, at least one section of each set being a square and one or more of the others an equilateral triangle, the map on the square sections being constructed on a two-way great circle grid and the map on the triangular sections being constructed on a threeway great circle grid.

A map of the world comprising six equilateral square sections and eight equilateral triangular sections matching along edges which are representations of projected great circles with uniform scale cartographic delineations along said edges. USA en. WOA1 en. Unified method and system for multi-dimensional mapping of spatial-energy relationships among micro and macro-events in the universe. Map profile of the earth's continents and methods of manufacturing world maps.

Polyhedral approximation of a spherical body and two-dimensional projections therefrom. This is a type of GraphSLAM, a pose graph optimization which works by building constraints between nodes and submaps and then optimizing the resulting constraints graph. When a node and a submap are considered for constraint building, they go through a first scan matcher called the FastCorrelativeScanMatcher.

Once the FastCorrelativeScanMatcher has a good enough proposal above a minimum score of matching , it is then fed into a Ceres Scan Matcher to refine the pose. For more detailed information on the algorithms involved, see the Algorithm walkthrough for tuning page.

A detailed description of the development of the simulated sensor is available here. Last, we will use the WillowGarage world as the simulated environment to operate the system and create the map. A sample image of the OS mounted on the racecar platform in the WillowGarage Gazebo environment is below:.

The first file defined is a. The robot configuration is read from a options data structure that must be defined from a Lua script. First, we will define the TF frame IDs of the environment and the robot. These coordinate frames are defined in REP This frame publishes the non-loop-closed local SLAM result.

We will be inputting the OS lidar data as a 2D laser scan. There is one global variable that needs to be configured based on the sensor properties. Explanations for the remaining values are detailed in the Lua configuration reference documentation. This link has two children. The specific rotations and translations between the components are also defined in the. These dimensions are taken from the OS1 Datasheet. The recommended usage of Cartographer is to provide a custom. For this simulation, we will be doing 2D slam with simulated IMU and laser scan data as inputs.

We also remap the IMU and laser scan data from their default topics to the topics output by the simulated robot and OS-1 sensor. Generating the map is expensive and slow, so map updates are in the order of seconds.

This file loads the simulation as well as all the relevant supporting ROS nodes to produce the required data for Cartographer to function. The first portion of the file defines default values for several parameters that can be used to customize the simulation.

These values can be overwritten via the command line when launching the simulation. Next, the Gazebo simulation is started by loading the appropriate world file and spawning the robot with its integrated sensors. Then several nodes are loaded that allow the user to control the robot via the keyboard or joystick.

This makes computation simpler and also increases the flexibility of the system. The video below shows the vehicle navigating the environment. Cartographer provides an RViz plugin which allows the visualization of submaps, the trajectory, and constraints.

Once the environment is sufficiently mapped the map file can be saved and it can be loaded later. This creates two files. The YAML file describes the map metadata, and names the image file. The image file encodes the occupancy data. An example image of the occupancy grid map is shown below:. The next step is to move from the simulated environment to the real world environment.

There will be some minor changes and parameter tuning to reflect the real world environment. The first step is to collect data from your environment.

Before running everything on the integrated RC car, we will collect data in a simpler and more controlled environment. In the first example, an OS is mounted to a cart with a laptop as shown in the image below. The cart was manually pushed around the office.

It is generally a good idea to run this tool before trying to tune Cartographer for incorrect data. It benefits from the experience of the Cartographer authors and can detect a variety of mistakes commonly found in bags. The tool can also provide tips on how to improve the quality of your data. There are a couple of changes from the configuration files used in simulation:.

Now that the Cartographer can run on real-world data, we can integrate Cartographer into a complete robotic system. For this example, we will mount the OS to an RC car platform. The vehicle can be operated remotely with an Xbox controller. All processing is done on a fitlet2 with an Arduino Uno providing commands to the motors for steering and throttle. This set-up closely mimics the simulated system used earlier. The EKF node computes the odometry information that is later sent to Cartographer.

When operating the RC car, we want to limit the amount of processing resources utilized by mapping so those resources can be used for other perception, path planning, or controls functions that may also be running. However, if we process the collected data offline, we are less constrained by runtime constraints. It does not listen on any topics, instead, it reads TF and sensor data out of a set of bags provided on the command line.

Cartographer operates in both a 2D and 3D mode. In contrast, the 3D pipeline estimates a trajectory of 6DoF x,y,z, roll, pitch, yaw poses by matching 3D scans in 3D submaps. With 3D SLAM, you need to provide an IMU because it is used as an initial guess for the orientation of the scans, greatly reducing the complexity of scan matching. This configuration subscribes to PointCloud2 topics instead of LaserScan messages:.

This results in the final trajectory and map being the most accurate Cartographer can provide. Cartographer serializes its internal state in a. Cartographer ignores most of the sensor data it processes so that it can run efficiently.

However, Cartographer allows for a combination of the mapping and trajectory information stored in the. When running Cartographer with an offline node, a. This can be observed when running the RC car example shown previously:. Alternatively, you can use the exposed Cartographer services explicitly finish the current trajectory and make Cartographer serialize its current state when running Cartographer in online mode.