The new senseFly Solar 360 UAV is designed to enable the automated and efficient inspection of solar farms.
Photo: SenseFly
SenseFly has introduced its senseFly Solar 360. Created in collaboration with software company Raptor Maps, the offering is an efficient thermal drone solution that enables the automatic assessment of solar plant performance at a sub-module level, the companies said.
Created by combining eBee X fixed-wing drone technology, senseFly’s Duet T thermal mapping camera and Raptor Maps’ software, senseFly Solar 360 is a fast and fully automated drone. It is easily integrated into solar management workflows without requiring either drone piloting skills or the manual analysis of aerial solar farm data.
“At senseFly we are continually looking across the industry to identify new commercial partners with whom we can bring to market what our customers need, which is vertically-focused end-to-end solutions,” said Gilles Labossière, CEO of senseFly.
“With Raptor Maps, we are collaborating with a true solar industry pioneer,” Labossière said. “Their software takes the guesswork out of solar farm inspection and, crucially, speeds up this process — from days down to hours. This efficiency, combined with the eBee X’s large coverage and reliability, ensures that farm owners and operators — or the drone service providers they employ — can inspect utility-scale solar farms more quickly, easily, and accurately than ever before.”
“Solar power is the largest source of new energy generation in the world,” said Nikhil Vadhavkar, CEO of Raptor Maps. “This rapid growth has fueled demand for industry-specific solutions to allow solar customers to scale. Our enterprise-grade software has been deployed across six continents and 25 million solar panels to increase power production and reduce risk and maintenance cost across solar portfolios. We are proud to collaborate with senseFly, the industry leaders in commercial fixed-wing drones, to increase access to Raptor Maps while providing a comprehensive, end-to-end solution that scales with the solar industry.”
JEDI-200 reduces the energy of getting one position fix by up to 150 times, according to the company.
Photo: Kolmostar
Kolmostar, a positioning technology company, has launched an ultra-low-power GNSS module at IoT World, which took place May 13-16 in Santa Clara, California.
JEDI-200 reduces the energy for one position fix by up to 150x compared to traditional GNSS sensors, providing a positioning solution for location-based internet-of-things applications, the company said.
1-second ultra-fast time to first fix from cold start
2-meter CEP high positioning accuracy
Supports GPS and Beidou constellations
100-byte compressed ephemeris (EPH) to enable A-GPS with speedy download via LPWAN technologies such as LoRaWAN and NBIoT
High-performance cloud computing based on 50-byte raw position files for optimized radio transmission efficiency and minimum endpoint power consumption
Integrated SAW filter, stand-alone LNA and TCXO
12 x 16 millimeter form factor for easy RF integration
“JEDI-200 supports GPS as well as Beidou constellations,” said Tao Tong, co-founder and CEO of Kolmostar. “While achieving industry’s lowest power consumption, it helps our customers to achieve high accuracy even in dense urban canyon environment where existing GNSS modules on the market often drift due to multipath and other errors.”
The JEDI-200 is designed specifically for IoT applications such as human and asset trackers (for bikes, scooters, vehicles, cargo, livestock, pets and more), smart wearables, smart farming and infrastructures,.
Its reduced level of power consumption and its optimized efficiency with LPWAN technologies solve IoT endpoint deployment’s pain-point of needing frequent recharges or a large battery, enabling new possibilities in location-based IoT applications.
Little Roady Shuttle to aid research on autonomous vehicle technology
Rhode Island officials have kicked off the Little Roady autonomous vehicle pilot project in Providence. The research project, which aims to evaluate autonomous mobility technology, begins service May 15.
The free service will be the focus of a research project to help the Rhode Island Department of Transportation (RIDOT) better understand the opportunities and challenges that come with integrating this new technology into its transportation planning. The research will help improve transit and provide information for communities, the workforce and policymakers.
The shuttles use a suite of sensors — including some from Middletown-based KVH Industries — and intelligent software to help the vehicle understand its environment and how to safely navigate through it.
The entire fleet has undergone 500 hours of testing both at Quonset Point this winter and in Providence this spring, which included detail mapping so the machines know every inch of its route and how to operate in a variety of traffic and weather conditions.
The Little Roady shuttles are provided by May Mobility Inc., which entered into a public-private partnership with RIDOT in the fall of 2018, following a competitive request-for-proposals (RFP) process.
“It’s always exciting when Rhode Island has an opportunity to lead the way in cutting-edge green technology,” said Governor Gina Raimondo. “This project will provide valuable data for states across the country as we move beyond conventional transit services to provide better, cleaner, and more accessible transportation for all.”
The experimental service will operate seven days a week, from 6:30 a.m. to 6:30 p.m., with 12 stops between Olneyville Square and Providence Station. The Little Roady shuttles will run on a continuous, 5.3-mile loop on low-speed roads with an average wait time of about 10 minutes. Trip time will be about 20-25 minutes each way from Providence Station to Olneyville Square.
“The kickoff of this service and research project is another achievement for the new DOT,” RIDOT Director Peter Alviti, Jr., said. “Our transportation agency has literally been rebuilt to effectively deliver safer roads and bridges while simultaneously studying and piloting new technologies. In doing so, we’ll keep Rhode Island well ahead of the curve for the transportation solutions of tomorrow.”
“By partnering with RIDOT, May Mobility is showing how our self-driving shuttles can be part of a sustainable future for communities,” said Edwin Olson, CEO and founder of May Mobility. “Our environmentally-friendly shuttles aren’t just fun-to-ride, they can increase access and convenience for a large number of people.”
The cost of the project, including the research component, is $1.2 million. This includes funding for an $800,000 public-private partnership with May Mobility, a $500,000 grant awarded by the R.I. Attorney General’s Office as part of a settlement with Volkswagen, federal research funds through the Federal Highway Administration, and matching state funds. RIDOT’s contract with May Mobility includes options to extend the service for an additional two years.
The debut of the autonomous vehicles is the latest step in a multi-agency effort called the Rhode Island Transportation Innovation Partnership (TRIP), which RIDOT launched in 2017. TRIP also includes a research component, with the goal of studying autonomous mobility solutions, ridership, workforce impacts, environmental impacts, and technology adoption, among others.
TRIP includes many partner agencies and governmental entities, including the City of Providence, the Rhode Island Public Transit Authority (RIPTA), the Rhode Island Division of Motor Vehicles and the Quonset Development Corporation. The research team is made up of representatives from Brown University, 3×3 Design, Stae, and Bits and Atoms.
May Mobility, a Michigan-based startup, is developing self-driving shuttles for college campuses, corporate clients, and central business districts. It launched a private corporate service in Detroit in June 2018 and a public service in Columbus, Ohio, in December 2018. It has also entered into an agreement for public service in Grand Rapids, Michigan. The company has hired fleet attendants and managers from Rhode Island and has set up a local operations office in Providence.
Featured photo: Rhode Island Department of Transportation (RIDOT).
We’ve all been there before: static on our wireless call or, worse, the call drops at the most inopportune time. Like instant response when we surf the web, consumers have come to expect clear, consistent call connections when using mobile. With too much of a bad thing, the churn risk soars to untenable heights.
5G, shorthand for Fifth-Generation Wireless Systems, holds the promise of transforming our daily lives. Using massive bandwidth, extremely low latency and high speeds, almost everything that requires sending and receiving data gets a boost. Unique radio frequencies transmitted with precise directions improve on the older 4G approach by taking advantage of higher frequencies. The signals take less time to transfer from one device to another, dramatically reducing wait times.
How does this help business and the consumer? Video conferencing is better, call connections are clearer, and smart homes get their Ph.D. How does this become reality?
Rather than using satellite-based towers, 5G depends on shorter signals using antennas and other transmission devices installed closer to the ground, on the tops of buildings and existing utility poles. Herein lies the rub. Ground features such as trees or tall structures can interfere with transmission. On top of this, there’s the need to plan for change. Vegetation grows over time, new construction takes place, and the cycle of interference continues. Imagine trying to plan a 5G network in an urban environment replete with hundreds or thousands of tall buildings. How would a telecom decide where to place the hardware and optimize the network?
The answer rests in aerial imagery, also known as aerial mapping. Rather than relying on satellite imagery that’s less clear and prone to atmospheric conditions, high-resolution camera systems mounted inside planes are photographing the world — all in 3D. Within predefined coverage areas, every point on and above the ground is being photographed and transformed into a variety of 3D models. For the telecom industry, planners can predict zones of interference and place hardware accordingly. They can better service their customers and quickly adapt to changing conditions in support of maintaining the network.
One type of output from these advanced camera systems is called a digital surface model, providing detailed elevation profiles of ground features, building, bridges, you name it. Also knows as DSM, the elevation detail contained within the imagery facilitates analysis to optimize the placement of 5G antennas and transmission devices.
When combined with other forms of imagery that allow users to clearly visualize every aspect of the landscape in photorealistic, immersive 3D, this enables telecoms to quickly model all the transmission permutations.
These high-tech companies use machine learning to identify clear signal areas and sections of the landscape where a tree, for example, may degrade the 5G radio frequency. Armed with such intelligence, strategic placement of hardware unlocks the optimized network — all without having to leave the office to collect data from the field.
The race is on to roll out 5G. Fortunately, advances in aerial photography have been combined with machine learning and artificial intelligence (AI) to speed up network planning and change modification. With tens of thousands of access points needed for large cities, advanced uses of aerial imagery and data science provide the answer for fast 5G deployment.
Less than a decade ago, mobile mapping systems were being designed and sold using computer systems that rivaled most desktop computers. Mobile mapping vehicles had to be custom-fit for large displays and computer systems, usually with large, expensive, bulky redundant arrays of inexpensive disk (RAID) storage systems that would consume the back of a van or, at the very least, the back seat of a car. Wiring for these systems completely entangled the vehicle, making it a dedicated part of the mapping system. Many of these systems are still being used today, as their utility is only lost on space consumed but not on usability or productiveness.
In 2019 we face the ever-increasing demand for smaller size with greater performance, especially in the instance of UAVs, where size, weight and power consumption are precious commodities.
Wires? Nobody wants or expects to see any wires or cabling running between devices, with the possible exception of power. A desktop computer, laptop or RAID system is no longer a consideration. Storage is replaced by high-speed, high-capacity media such as Compact Flash, Flash memory cards, and solid-state drives.
And all of those wires? They are replaced by Wi-Fi or Bluetooth working directly between the onboard microprocessor (at most the size of a deck of cards) and what else? Your cell phone. Maybe a tablet.
The inertial navigation system inside these UAVs, the central nervous system of a mobile mapping set-up, can no longer afford to weigh several kilograms. It must weigh under 1 kilogram, with less than 500 grams preferred. The accompanying antennas must also shrink.
At the same time, cost must drop while performance must be maintained or improved. More users will adopt the technology, and they will no longer be experts. Reliability and durability will be of utmost importance.
The autonomous SnowBot Pro is ready to clear your walkways. Offered by Left Hand Robotics and guided by Swift Navigation, it is a commercial-grade, robotically driven product for snow removal.
Driving autonomously, SnowBot Pro clears snow from walkways with a 56-inch-wide rotating brush, reducing the number of hand shovelers or snow blower operators needed by up to 80 percent, the companies said. Various front and rear attachments allow for a multitude of tasks, such as snow removal in the front and deicing in the rear. It also reduces potentially costly slip and fall insurance claims.
The SnowBot is programmed and controlled remotely from the cloud via an online dashboard or mobile app, and follows its programmed path using GPS, accelerometer and gyroscope technologies for navigation.
Sensors detect any obstacles and can instruct the robot to stop to avoid collisions and send instructions about how to bypass obstacles. Location, weather and robot status data is recorded in real time, along with before and after photos. The detailed recording helps minimize insurance and risk-management costs while providing customers with proof of work.
The robot has to navigate precisely, avoiding potentially damaging landscaping, walls, curbs and other obstacles along sidewalks and walkways. Centimeter-level GNSS ensures it avoids obstacles and stays on its designated route. Finding a reliable real-time kinematics (RTK) GNSS solution was critical given that many sidewalks are near buildings and underneath trees.
After evaluation, Left Hand Robotics chose Swift Navigation’s Piksi Multi. Its centimeter-level accuracy keeps the robot in its designated path and allows its base robot platform to navigate in a variety of environments, whether in lines (sidewalks, bike paths) or large open areas (fields, parks). The Piksi Multi also retains a GNSS fix in challenging conditions and environments.
Once Swift’s ruggedized Duro receiver was launched — and could be used by customers as a base station that was required for RTK — Left Hand Robotics had a complete offering for customers, which it launched in the winter of 2018–2019.
A Piksi Multi is installed in each SnowBot Pro, and its Path Collection Tools (tools customers use to collect the initial path data the robot will follow) and Duro is used as the base station controlling the SnowBot Pro robot.
A tool developed by Mapbox explores “10 years of OpenStreetMap.” During that decade, hundreds of thousands of people mapped 25 million miles of roads in every country in the world.
The internet tool uses a slider to show the data change over time. You can see additions and edits as they come online over the decade — a fascinating look at the intricate information that has been compiled. When a user drags the slider to the left, it’s easy to see how scant the information was only a few years into OpenStreetMap’s existence (the image at right shows the same European region in 2009 as the image at the top in 2015).
The same European region in 2009 as the image at the top in 2015. (Image: OpenStreetMap)
After GPS and GNSS, OpenStreetMap ranks high in the movement to make geographic information accessible. OpenStreetMap is a community-driven project to create the most detailed, correct and current open map of the world.
When Steve Coast began the project in 2004, map data sources were few, and largely controlled by private companies and the government. Coast changed the rules by creating a wiki-like resource of the entire globe, which everyone could use. Today, 5.2 million people use OpenStreetMap.
OpenStreetMap democratized mapping: all a contributor needed was time and a computer connection to add data about their country or their neighborhood. Besides GNSS, contributors use aerial imagery and low-tech field maps to verify that OSM is accurate and up to date. Others dedicate their energies to humanitarian projects, including disaster response following the Haiti hurricane and aiding South Sudan and Syrian refugees.
The Trimble CenterPoint RTX correction service, enabling centimeter-level absolute positioning around the world without the need for RTK reference-station infrastructure, is now available to many users, including integrators of professional high-precision equipment and consumer products such as in the automotive sector. Access is provided via a software library compatible with any GNSS device. The corrections now contain detailed integrity information for safety-critical applications.
The RTX infrastructure is made up of approximately 120 globally distributed RTX reference stations. Receivers at these stations transmit measurement data at 1 Hz to the RTX server centers, where the correction data is computed. For redundancy purposes, multiple servers in the United States and Europe are operated. A failsafe architecture avoiding any single point of failure in the processing chain has produced a very high availability of corrections. Today the system supports GPS, GLONASS, Galileo, BeiDou and QZSS satellites. It is a multi-frequency system supporting two or more frequencies for each satellite system.
The correction stream is available to users using L-band signals broadcast via geostationary satellites and IP connections. The L-band transmitted RTX data stream uses a bandwidth of 600–2400 baud, and a highly compressed data format with a resolution of 1 millimeter, with an average latency of 8 seconds in L-band mode and 5 seconds in IP mode. The data stream is encrypted via an Advanced Encryption Standard (AES) with a key length of 256 bits to guarantee safe transmission. Data transmission integrity is assured with a 32-bit cyclic redundancy check attached to every message. The RTX correction stream provides information on satellite position, satellite clock, ionospheric and tropospheric models, and code and phase biases.
The orbit determination is done in real time using a reduced dynamic approach with dynamic models and exploiting the accuracy of the phase measurements after ambiguity fixing. Based on the computed orbits, the satellite clocks are estimated at 1 Hz, where integer ambiguity fixing is performed for the different satellite systems.
Next, a single-layer global ionospheric model is computed and represented through spherical harmonics. There are currently two areas with a denser network than the global network; these cover Europe and the mainland U.S. with more than 1,000 base stations. Using these stations, regional ionospheric and tropospheric models are computed, which then provide a fast convergence (RTX-Fast service).
The satellite position and clock information has centimeter accuracy and allows the client to compute precise point positioning (PPP) with carrier-phase ambiguity resolution. Table 1 shows service accuracy.
Table 1. Accuracy of the RTX corrections from more than three years (June 2015–July 2018) of residuals computation in the European RTX-Fast network. (Table data: authors)
Once the ambiguities are resolved, the position solution is accurate to a few centimeters. The global RTX-Standard service provides convergence times of 7 minutes to 20 centimeters (cm) horizontal error (95%) and to 2.5 cm (95%) in 13 minutes as shown in Figure 2. The regional RTX-Fast service (U.S., Europe) provides convergence times of less than a minute with centimeter accuracy. The warmstart convergence time is approximately 13 seconds.
Figure 2. Global convergence of RTX out of 52 globally distributed stations covering one month of data. (Image: Trimble)
The accuracies specified are achievable with precise Trimble GNSS positioning hardware. For integration into non-Trimble devices, an RTX software library is offered, which gives the user real-time access to the individual data in the RTX correction stream. For use of this library in safety-critical systems such as advanced driving-assisted systems (ADAS) or semi-automated driving, this library was certified to follow the ASIL-B ISO 26262 standard and the automotive ASPICE standard. This library is available for easy integration into third-party applications.
In addition to the real-time RTX solution, a web-based post-processing solution is available for public use free of charge. It is possible to upload static Trimble or RINEX files to the server, post-process the measurement data, and retrieve a precise position in various coordinate frames.
Service integrity is continuously monitored at independent stations from the RTX tracking networks in Europe and the US. The integrity of the service is provided at the correction data domain. The integrity monitoring part of the RTX system minimizes the risk due to events such as unplanned satellite maneuvers or wrong broadcast ephemeris; satellite signal or clock anomalies; ionospheric storms; or problems in transmitting the RTX correction stream.
The monitoring stations compute phase observation residuals (with ambiguity fixing) using the station measurements and the received RTX corrections. These residuals represent the actual errors of the corrections as seen by the monitoring stations at the line-of-sight (Table 1). The thresholds at which corrections are considered as faulty are the following: 0.5 m + QI (quality indicator) for orbit + clock corrections and regional tropospheric models, and 1.0 m + QI for regional ionospheric models.
The integrity monitoring consists of two steps (Figure 1): a pre-broadcast check, where potentially faulty corrections are detected and filtered out before leaving the computing server, and a post-broadcast check, where additional errors in the transmission channel are detected and alarms are issued to the users.
Figure 1. Generation and transmission of RTX global and regional corrections, including pre- and post-broadcast integrity monitoring. (Image: Trimble)
Integrity flags and alarms are constantly inserted into the correction stream and output by the RTX client library. The integrity information notifies clients of the presence of integrity monitoring and provides timely alerts in case of detected correction-data integrity violations. The time-to-alert limit goals are 17 seconds for L-band transmission and 13 seconds for IP transmission for the RTX service.
The RTX corrections includes quality indicators. In particular, the quality indicator for the satellite clock includes a “DoNotUse” flag to indicate potential problems with the given satellite. This flag prevents the use of the satellite for positioning when received by the user. The quality indicators of the corrections are indeed a first integrity layer. In 2017 the pre-broadcast integrity monitoring was added to act as a second layer. In 2019, with the addition of the post-broadcast integrity monitoring, a third integrity layer was added to the RTX correction data stream.
The RTX system provides access to centimeter-level corrections allowing centimeter positioning on a global basis. RTX-Fast services are available in Europe and the U.S. with pre- and post-broadcast integrity monitoring currently being deployed.
The authors are engineers with Trimble Terrasat GmbH, Germany.
Auterion and Impossible Aerospace are collaborating to bring to market the US-1 UAV, which has a two-hour flight time.
Auterion is the provider of Auterion Enterprise PX4, an open-source-based, enterprise operating system for drones. Impossible Aerospace is Silicon Valley, California-based drone manufacturer on a mission to assemble the highest performance electric aircraft.
“During critical public safety incidents, real-time intelligence from a UAV is extremely important. This is why the two-hour flight time of the US-1 is a clear necessity.” said Spencer Gore, CEO of Impossible Aerospace. “We turned to Auterion for software because their operating system is auditable and trusted for government applications.”
“Public safety organizations can now field a drone with government solicited, cyber-secure and trusted software that enables the drone to stream real-time footage to a command center,” said Kevin Sartori, co-founder of Auterion. “Choosing Auterion and its open-source, open-standards approach will greatly simplify the integration of the US-1 into the IT-infrastructure of public safety organizations.”
Thousands of professional drone pilots and businesses around the world count on open-source flight control software PX4, which was created by Auterion co-founder Lorenz Meier in 2011 and has evolved into a global developer community. Similar to Red Hat, Auterion builds the open-source infrastructure so that drone manufacturers can go to market faster with new products flying trusted software.
The US-1 quadcopter made its public safety debut in February with a California-based police force. The drone gives police agencies a new category of assets that sit between lower-end drones and police helicopters. This enables a wider usage of aerial imagery and reduces the cost for first responders at the same time.
Shanghai-based GNSS technology and solutions company Shanghai Huace Navigation Technology Ltd. — known as CHC Navigation — has opened a North American subsidiary, CHC Navigation USA Corporation, in Scottsdale, Arizona.
CHC Navigation was established in 2003 and was ranked as one of China’s top GNSS and RTK technology and solutions companies in 2017. It has customers in more than 100 countries worldwide and has been providing GNSS and RTK products and solutions to the US marketplace since 2009.
The establishment of a North American head office in Scottsdale illustrates CHC Navigation’s ongoing commitment to expanding its products, services and customer support in the U.S. and North American marketplaces.
CHC USA will warehouse, sell and service from Scottsdale all of its products to its dealer and OEM network of customers across North America. With the new U.S. presence, CHC USA will be able to respond more quickly to its dealer and customer order requests and service requirements.
CHC USA specializes in CORS GNSS base-station infrastructure, deformation monitoring, surveying and mapping. With new 3D lidar scanning and hydrographic unmanned survey vessels launching later this year, CHC USA’s North American office and team members will continue to focus on ensuring a great customer experience.
“On the heels of strong CHC Navigation growth in the US in 2018, the time was right to establish a domestic US sales and service office and warehouse with a local team of positioning industry professionals,” said George Zhao, CEO of CHC Navigation. “Our U.S. and Canadian customers have been very supportive of CHC Navigation over the years and our focus will continue to be on providing industry leading products and services to our valued North American dealers and customers,” added Phil Gabriel, President of CHC Navigation USA.
Topcon Positioning Group is offering a new edition of its real-time 3D job site monitoring and management system, Sitelink 2.0. The update includes a new pay-as-you-go point-based service model, new features to Sitelink Support Desk, as well as a new Haul Truck application, the company said.
Version 2.0 includes a newly redesigned web portal that features a consumption-based “Service Point” investment model.
“We are introducing a completely new way to service our customers that allows them to take advantage of a pay-as-you-go account-based system rather than year-long pre-paid subscription-based plans,” said Murray Lodge, senior vice president, construction. “With no expiration date on the Service Points, contractors can be assured their investment will be protected in their personal account and allocated when it best suits their needs.”
Also, new to the service includes remote configuration functionality in Support Desk. It allows Topcon support personnel to directly access and configure receiver components on connected machines, while simultaneously retaining an active remote session of the 3D-MC machine control software.
“We have made support more efficient with less downtime for operators with our team having the ability to go straight into the configuration settings for receivers and make adjustments, minimizing work stoppage on the site,” said Lodge.
The latest version also includes a new Topcon Haul Truck application, which utilizes an Android or iOS app that can be installed on a phone or tablet. It is designed to provide a complete and easy-to-use cloud-based, haul management and reporting system with real-time visibility.
“The new Haul Truck app provides productivity statistics for each haul, including the counts, average distances and the time it takes to complete the process — all within a geofenced pickup site and unloading zone. It is simple to use — drivers come onto the site, quickly enter basic info and get to work,” Lodge said. “With 3D map imagery, operators can view where the load is being picked up and the path it takes to unload and return, and it automatically records for reporting.”
Geneq Inc., a manufacturer and provider of GNSS receivers and positioning solutions to GIS professionals and surveyors, has launched its newly designed website. The website features new functionalities, better product viewing options, and improved product support options.
The completely redesigned website to support the company’s product and service improvement program, the company said. The new website will be regularly updated with news on SXblue products, product support, software updates, events and social media feeds. The company welcomes feedback from clients, distributors and partners.
Geneq Inc. has been developing and manufacturing professional GNSS receivers and software products for 15 years. Its SXblue brand has been sold around the world.
AgJunction Inc. is partnering with Swift Navigation to develop near-autonomous small tractor solutions for agricultural applications with high accuracy.
The Duro enclosure. (Photo: Swift Navigation)
The partnership will combine autosteering technology pioneered by AgJunction and the Duro RTK GNSS receiver from Swift Navigation. The research resulting from this partnership will ultimately lead to lower cost autosteering products with high accuracy, the company said.
“Duro, and the robust RTK GNSS positioning it delivers, is a source of pride for Swift,” shared Tim Harris, CEO of Swift Navigation. “With a mission to enable a future of autonomous vehicles, we strive to bring that autonomy to farm equipment — such as small tractors — at an affordable price for farmers and partnering with the renowned autosteering expert AgJunction helps make that a reality.”
“AgJunction and Swift have been groundbreaking in their respective fields,” said Dave Vaughn, president and CEO of AgJunction. “I’m eager for what the future holds and how we can further deliver low-cost autosteering and navigation while delivering high accuracy down to a centimeter.”
