RTK GNSS module for precise
navigation and UAV mapping
Shipping in May 2018
Reach now works on a new processor and is called Reach M+. It comes with locking connectors and a protective plastic case. Fully compatible with the previous version, Reach RS and Reach RS+.
Reach calculates real-time coordinates with centimeter accuracy
and streams them in NMEA or binary format to your device
over UART, Bluetooth or Wi-Fi
Reach module logs precise tracks and the exact moment
when each photo is taken
Usually autopilot triggers the camera and records the coordinate it has at the moment. When the drone is flying at 20m/s and GPS works at 5Hz, that means your autopilot will have position readings only each 4m. While enough for navigation such readings are not suitable for precise georeferencing. Also, there is always a delay between the trigger and the actual moment the photo is taken.
Reach module solves this by directly connecting to the camera hot shoe port which is synced to the shutter. The time of each photo is logged with a resolution of less than a microsecond.
Every time a photo is taken camera produces a pulse on a flash hot-shoe connector which is synced to a shutter opening.
Reach captures flash sync pulses with sub-microsecond resolution and stores them in a raw data RINEX log in internal memory.
After the flight get the RINEX logs from your airborne Reach module and a base station (Reach RS, CORS or other receiver).
Process RINEX files using the free RTKLIB software. Produced file with precise coordinates of the photos can be used for georeferencing.
Luke Wijnberg, 3DroneMapping
As a brief synopsis of the results, the maximum deviation of points was no more than 0.09m in all axis. This is an incredible result given the fact that the average pixel size of the resulting imagery was 0.045m. It is interesting to note that the average mean error in all axes is 0.00m!Read more
Brian Christal, Tuffwing
Tuffwing recently performed integration of Emlid Reach RTK to enable making precision maps without use of GCPs. The system was benchmarked by comparing direct georeferenced model with a set of GCPs, used solely for error detection purposes. Achieved lateral RMS error is just 4cm according to the Pix4D quality report.Read more
Jeff Taylor, Event38
In this case study, we produced an orthomosaic in the Drone Data Management System™ with 2.45cm horizontal and 5.08cm vertical RMSE, as compared with a survey-grade GPS on the ground.Read more
Luke Wijnberg, 3DroneMapping
3DroneMapping has been testing a PPK system for the past year to itegrate into our daily workflow. The point of PPK (or Post Processing Kinematic) is not just to improve internal photogrammetric model orientations, but also is general recognised as a way of undertaking full scale surveys at the same accuracy but without having to place time consuming ground control points. 3DroneMapping setup a calibration site to test the claims made by the manufacturers and ultimately for our own quality assurance that what we publish is indeed right the first and only time.
Ground control points traditionally have become a sore topic with RPAS aerial surveyors as they take time to construct, survey and verify. These points are needed in a much greater density than tradition aerial survey methods, due to the non metric cameras often used in RPAS. Locations where the terrain changes rapidly, homogenous surfaces, and densely vegetated areas all require a higher density of control points to assist the photogrammetric software to locate accurate ties points and stop the model from deviating. Undertaking a photogrammetric survey without control, can lead to disastrous results, as outlined in a previous article, “GROUND CONTROL VS NO CONTROL”
There are a number of issues with placing and surveying control points. The obvious one being that another piece of survey equipment is needed to accurately record the positions. This comes at a great cost as survey grade GPS systems can run into tens of thousands of dollars. Then the areas for the control need to be identified. These areas are often located at the fringes of the site to be surveyed as well as in the center. This means that the site needs to be traversed (often on foot) to place marks and survey them. In some cases it can take a few days to complete the marking for fairly small sites due to the terrain, vegetation, etc. Control points are also not permanent. They often go missing due to weather, theft for vandalism and cause problem for the surveyor back in the office when the surveyed points are not visible on the imagery.
Another problem with using control only for surveys using low level photogrammetry is that the consumer grade cameras used are not metric and are prone to distortion. While control can eliminate this to an extent, it is the areas between the control points that often are forced to fit alignment. This can lead to errors especially regarding heights.
Emlid has produced35 and excellent L1 only reciever that is sure to revolutionise the Small Unmanned Aircraft photogrammetry sector. Coupled to a decent camera with a good lense and sync cable, the setup allows you to undertake surveys to mean accuracies of less than 10cm. All that is required is a base and a rover (2 devices) that log the data for you in an easy to operate webviewer. No need for external comminication radios, or fancy antennas, only a steady 5v supply like a battery bank.
PPK is setup to have an accurate onboard GPS system that records a high frequency measurement tracklog of an RPAS flight. The system notes every time the camera takes an image and logs it. Another GPS is setup on the ground to record satellite information during the flight. Using a fork of RTKLib, Emlid has developed their own flavour of this powerful piece of software that takes into consideration each time the shutter is trigger and records the position of that event. The timing of such an event is crucial, as a few milliseconds delay can translate to a few meters when operating at speed. The software compares the relative satellite positions between the devices, resulting are very accurate coordinates for each image captured.
The photogrammetric model generated from using PPK enhanced images gives a much more consistent and accurate rendering of the terrain. Tie points have a much greater certainty of intersection, speeding up the matching processes. This reduction in uncertainty means less resources are required, leaving an opportunity to increase the density of other processes like point cloud generation, geometrically verified matching, etc.
Trials for PPK testing for 3DroneMapping began 3 weeks ago with a test calibration site. Over 200 tradition ground control points were surveyed over a 780ha site, some of which were placed in very challenging positions that like close to tall structures, under power lines, close to dense vegetation and visibly homogeneous surfaces. The control points were placed over 18 months and maintained. The site was flown over a 3 week period with a number of flights and post production methods to determine the optimum settings and processing requirements. At the end, the most consistent and repeatable results were chosen for the optimised settings for the end survey requirements and RPAS setup.
Control points were digitised from resulting point clouds and orthophotos and compared to the previously surveyed. These positions showed almost no difference to the control as published. Areas that have previously been a problem for photogrammetry showed up even and consistent between surveys when drawing profiles or cross sections. The 200 control points varied only a few centimeters over the entire site giving a very accurate and tight model.
As a brief synopsis of the results, the maximum deviation of points was no more than 0.09m in all axis. This is an incredible result given the fact that the average pixel size of the resulting imagery was 0.045m. It is interesting to note that the average mean error in all axes is 0.00m! But this is meaningless as it is an average across the field. The maximum deviation measured between session as a profile or cross section indicated almost no shift at all, meaning that the data is consistent between sessions. This is close to impossible under normal operations with ground control points.
The aircraft used was a fixed wing RPAS carrying a Sony camera with fixed focal lense A total of 836 images were collected at 800ft AGL, with a 68% side and overlap. The test area is 780ha big and takes 45-55 min to fly at an average speed of 19m/s. The Reach was recording data at 14hz, GPS only. The ground survey completed with Leica GPS1200 checked measurements to 0.02m horizontal and 0.03m vertical accuracy with all points checked and meaned.
— PPK setup using Sony A6000 camera, 20mm lense, EMLID Reach with flash sync, Tallysman TW4721, ReachView beta v2.1.5
— PPK base running EMLID Reach, TW2410, ReachView beta v2.1.5
— PPK post processed in RTKPOST ver2.4.3_Emlid_b26
— Photogrammetry done in Pix4Dmapper Pro Ver 3.0.17
— Orthophoto resolution 0.043m, point cloud resolution 47.1 points per m³
— Comparison digitised in ArcGIS V10.0
— EPSG:2054. Hartebeesthoek94 / Lo31
What this all translates to is that surveys can now be undertaken with even less time spent in the field and can result in even more accurate and consistent data. But should you not place control at all? This is a bad survey practice as you are depending on only 1 set of data measurements. As a caution, we would still place only a few control points as a quality assurance test to prove to yourself and others about the precision of the data generated.
But you do not need to buy or hire a GPS for this as the very same Emlid Reach35 in the aircraft can be used to survey those control points just as accurately!
Brian Christal, Tuffwing
Map georeferenced with Reach GPS data:
Tuffwing, a manufacturer of affordable aerial mapping systems recently performed integration of Emlid Reach RTK to enable making precision maps without use of ground control points. The system was benchmarked by comparing direct georeferenced model with a set of GCPs, used solely for error detection purposes. Achieved lateral RMS error is just 4cm according to the Pix4D quality report23.
Setup for surveying drone with Reach RTK and Tuffwing hot shoe:
The key feature of the setup is use of Reach RTK and Tuffwing/Reach RTK hot shoe cable together connected to the camera's hot shoe (Fig.2). This cable powers Reach rover, triggers camera from Pixhawk and directs flash sync pulses to Reach. Exact moment of each pulse is stored as time mark in the Reach RINEX files. No configuration for the Reach hot shoe cable is required, the camera will automatically trigger the hot shoe and the Reach will automatically record events down to fractions of a millisecond. This process does not require communication between autopilot and RTK receiver.
After the flight the time marks are converted into geotags with a free RTKLIB software provided by Emlid and are used for direct georeferencing of images. Commercial software such as Grafnav will be efficient as well.
To validate performance of the system Tuffwing organized flights using their Tuffwing UAV Mapper drone with Reach RTK GPS onboard. 112 photos were acquired with a Sony Nex 5T with Sony 16mm lens triggered by a Pixhawk.
Information about acquired data:
— Altitude: 100m
— Average Ground Sampling Distance (GSD) 2.82 cm / 1.11
— Area Covered 0.1139 km2 / 11.3916 ha / 0.044 sq. mi. / 28.1638 acres
Comparative quality report prepared in Pix4D by Tuffwing was based on geotag file from Reach RTK and GCP-file for validating the accuracy of 3d map. It is showing that the RMS error for Y-direction is about 4 cm while X-direction is less than 3 cm. All the data with detailed manual for processing the report is available, you can find links in the end of the article.
Tuffwing is now working on documentation to show complete data processing workflow.
Jeff Taylor, Event38
The PPK GPS system as integrated into the E384/6 is capable of delivering high scale accuracy when used alone and high absolute accuracy when a known good point is available near the flying site. In this case study, we produced an orthomosaic in the Drone Data Management System™ with 2.45cm horizontal and 5.08cm vertical RMSE, as compared with a survey-grade GPS on the ground.
For this study, a high resolution orthomosaic was created and multiple ground control points (GCPs) were collected to check the results. The orthomosaic was built using only the geotags from the onboard GPS.
The orthomosaic was built using an E384 outfitted with an Emlid Reach GPS Receiver and a Sony QX-1 Camera. The QX-1 was modified by Event 38 to provide the time that each image was taken down to one millisecond. Having this accurate timestamp is what allows the geotags, and subsequently the orthomosaic to be reconstructed with a high degree of accuracy. After the flight, we processed the RINEX file using an Event 38 utility and RTKLib postprocessing software. These produced a geotag file with coordinates for each image. Then the images and geotag file were uploaded to the Drone Data Management System™ to build the orthomosaic and DEM.
The GCPs were measured using a Trimble R6 Model 4, with corrections provided by the Ohio Department of Transportation (ODOT) VRS network. On the day of the flight, the Trimble R6-4 was not present. Instead, the Emlid Reach base station was positioned on a marker that had been previously recorded.
Once all the data was compiled, the orthomosaic was visually inspected and each feature representing a GCP was marked manually. Finally, we measured the distance between each marked GCP and the actual GCP location as measured on the ground.
Table 1 contains the full list of errors for each GCP, both horizontal and vertical. What we found is some variance in individual measurements, with up to 4.29cm horizontal and 6.7cm vertical error. Overall the RMSE was 2.45cm horizontal and 5.08cm vertical.
Table 1 - Errors between GCPs as measured from the orthomosaic vs on the ground:
The errors determined from this case study should be considered as characteristic of the Emlid Reach system when used with an E384/6 and QX-1 for measurements relative to the base station. In this case, we positioned the base station at a known good coordinate, so we were able to match the absolute GPS coordinates collected by the Trimble R6-4 very closely. When using the Emlid Reach by itself, even when using an outside correction system such as the ODOT VRS network, it is still possible for a significant offset to be present. The data will be accurate relative to the base station, but an offset between the Reach’s calculated base station coordinate and the true coordinate may exist. If the base station position is marked, it is possible to correct the absolute position at a later time.
At least some of the variance in error is due to the difficulty in locating certain markers accurately at the collected 2.5 cm/pixel ground sample distance (GSD). Although it is likely possible to improve this by collecting data at a lower altitude, we felt it was important to characterize the accuracy at a normal flying altitude which is more typical for our customers working in surveying, mining, and agriculture.
Based on this data, with RMSE errors of just 2.45cm horizontal and 5.08cm vertical, we feel confident that the PPK GPS system as implemented in the E384 and E386 can deliver reliable scale accuracy when used by itself and absolute accuracy when used in conjunction with a known good coordinate.
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Logs are automatically recorded in internal memory. View a list of the logs and download them using the ReachView app.
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Shipping in May 2018.
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Shipping in May 2018.