The latest safety award for Rivian is an Insurance Institute for Highway Safety for the R1S as a Top Safety Pick+ for 2023. It accomplishes this and other safety advances with its Driver+ ADAS (advanced driving assistance system), which integrates a set of sensors along with driver attention, GNSS, and IMU modules. At AutoSens Detroit 2023, Abdullah Zaidi, Engineering Lead and Senior Manager at Rivian, presented his take on the state and near future of ADAS sensors including the benefits of adding lidar and the importance of better localization sensors for Level 3 systems.

“It is very important for a vehicle to know its location within the geometric space,” he said.

With GNSS modules, he added that proper design of the RF (radio frequency) hardware and antenna are key, with the industry increasingly turning to more RF modalities. Since GNSS signals can get jammed or interfered with on a vehicle, he believes that the RF hardware should be kept separate or designed in a way that it doesn’t see a lot of interference.

The best possible GNSS accuracy is needed.

“The way you get it is by having access to more constellations as well as more frequencies,” he said. “Today, the non-high-precision GNSS generally use [the] L1 band but moving forward there’s a trend that the GNSS suppliers are transitioning towards using all three of them.”

Having access to L1, L2, and L5 bands is key for ADAS systems.

“It’s important to have access to all those frequencies and make sure there are no issues or inaccuracies due to the multipath or one of the frequencies not being available all the time,” he said.

He believes that more work is needed on GNSS redundancy for Level 3.

“Today most of the GNSS receivers aren’t ASIL B-qualified,” said Zaidi. “Moving forward, you would want to know that your GNSS is failing so the other sensors can take over, and that’s where the ASIL B is important.”

For inertial measurement sensors, low bias instability is needed for optimal dead reckoning.

“Vehicles generally dead reckon when you’re going through the tunnel, and the IMU is the one that helps you fail safely,” he said. “So, you have to ensure that your IMUs have a higher accuracy and they don’t drift a lot in the yaw dimension.”

In this regard, he believes MEMS technology is being used effectively for IMUs, but that a promising trend is for companies to move to fiber optics or silicon photonics. Careful consideration must be given to the vehicle packaging location of the IMU for reducing temperature changes and vibrations.

“Otherwise, that impacts the performance of your vehicle staying in the lane,” Zaidi said.

Like with GNSS, redundancy with IMUs is key. “If one of those IMUs fails, then you don’t have a backup to fall to in the scenario where you are aiming for a fail-safe operation,” he concluded.

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Santa Clara, CA-based startup Anello Photonics has announced a GNSS INS module that it says is the world’s smallest optical gyro inertial navigation system for GPS-denied navigation and localization. It is powered by the company’s optical gyroscope technology and AI-based sensor fusion engine, the combination engineered to deliver high-accuracy positioning and orientation for applications in the agriculture, construction, robotics, and autonomous vehicle space.

“We are actively engaged with customers who need robust, high-precision optical gyro-based solutions for their autonomous applications,” said Dr. Mario Paniccia, CEO of Anello Photonics.

Anello was co-founded by Paniccia and CTO Mike Horton, pioneers in the field of silicon photonics, sensors, and navigation, with the early support of Catapult Ventures and high-volume fab Tower Semiconductor. Coming out of stealth at CES 2023, Anello displayed the low-noise and -drift SiPhOG™ sensor, which it says is the first silicon photonics optical gyroscope and the smallest optical gyroscope in the world.

“It was a very ambitious thing we took on—creating a fiber gyro on a chip,” Paniccia to Inside GNSS. “We’re measuring a very tiny signal and putting it all into a standard process that’s fabricated in a high-volume fab. To our knowledge, no one’s building or has anything working at this level, let alone full INS systems, with integrated photonics.”

According to Anello, the silicon photonics optical gyroscope technology can be board-mounted and is made with integrated photonics components so it can be processed in high volume just like other integrated circuits. Another key advantage is a low unaided heading drift of less than 0.5°/h.

“This is the sweet spot,” said Paniccia. The MEMS in mobile phones and AirPods—which range from 2.0°/h, with high temperatures pushing that to hundreds and potentially a thousand degrees per hour—are not accurate enough for the autonomy safety case, he added. Typical fiber gyros, “the gold standard” for accuracy, are too big, bulky, and expensive.

“The idea is to bring the performance of high-precision optical gyros from guided missiles and other high-end applications into a form factor and price point that you can put it into the volume market in the autonomous landscape,” he said.

For the new GNSS INS system, the company launched an evaluation kit about a year ago for customer trials.

“It’s the smallest in this case, [with] not only the smallest gyro that we’ve developed and announced but now we have the smallest inertial navigation system that can be put into real solutions and real applications,” said Paniccia.

The near-term markets for Anello’s technology are in construction and farming “where they can pay a little bit of a premium.” An upcoming robotics product uses basically the same core fundamental platform without GPS.

In the future, the company is working to deliver to the high-volume auto market, and that means not only ASIL-D specs but also immunity to temperature and vibration with lower power consumption.

“We’re trying to gear towards ADAS (L2 plus, L3) over time,” concluded Paniccia.

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Earlier this year, FocalPoint Positioning announced a collaboration with General Motors on the possible application of the UK GPS software company’s Supercorrelation software in future vehicles, including potential enhancements and operational expansion of its Super Cruise hands-free ADAS (advanced driving assistance system) and its upcoming higher-tech sibling Ultra Cruise.

Supercorrelation enables a new class of satellite positioning receivers that can measure the directions of the incoming signals, allowing them to ignore reflected and fake “spoofed” signals. Manuel Del Castillo, VP of Sales and Business Development at FocalPoint Positioning, explained to Inside GNSS that the company’s technology focuses on line-of-sight signals with a unique way of analyzing the Doppler frequency.

“FocalPoint’s solution can predict that doppler and make the antenna work as a synthetic, smart antenna,” he said. “You can do that for all the different angles-of-arrivals of the GPS signals that you’re expecting. That allows you to focus on what you should focus on, and you’re not listening to all the other reflections that come from different angles that are not legitimate.”

That means a GPS chip can compute a position in an urban scenario as if it was on a highway by mitigating the effect of reflections “by a large amount. If you have generally around 20 meters of error, you would get it reduced to around 3 or 2 meters of error,” said Del Castillo.

Much of FocalPoint’s work with General Motors is confidential, but Del Castillo provided some interesting context. He said that the automaker is looking to apply the Supercorrelation solution because it’s a more cost-effective approach.

“Others are suggesting solutions that involve a lot of different hardware pieces that are much more costly,” he said.

GPS is a crucial element used by the ADAS to allow driving handoffs between the human driver and the system. The automaker’s engineers want to use Supercorrelation to extend the use of their systems from highways to cities.

“Right now, they cannot do it because GPS is not reliable enough in cities due to reflections,” said Del Castillo. “We’re facilitating the extension of Super Cruise to urban areas.”

The FocalPoint cooperation with General Motors is generating interest from other OEMs.

“They see it’s a cost-effective way of extending ADAS to cities, and others are seeing the same story,” he said. “We’re in that process with many OEMs right now. It’s very promising, but the challenge for FocalPoint is speedy execution because the supply chain is pretty complex.”

That execution involves convincing not only the OEMs but also the Tier Ones and GPS chipmakers that Supercorrelation should be embedded. The chipmakers include key names like Qualcomm, STMicro, and U-blox. FocalPoint has announced a partnership with U-blox, while many others are evaluating the technology.

The fact that it’s a software solution helps the cause.

“Software is the name of the game right now in automotive,” Del Castillo said.

FocalPoint’s entry into automotive is linked to the success of high-definition maps, he said.

“With an error of about 20 meters in a city, it didn’t make sense to have a map with all the lanes in a street,” he said. “With our technology, we are at the point that we can locate the car in the correct lane.”

He credits the work of Google, Here Technologies, and TomTom, as well as General Motors and other OEMs in bringing in the “lane-by-lane” HD maps.

“We’re going in hand-by-hand with the HD map suppliers because there’s a lot of synergy in what we’re proposing,” he concluded.

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For passenger car companies developing advanced driver assistance and automated driving systems, absolute positioning is critical to the overall solution. However, providing cost-effective systems is key for high-volume applications from price-conscious automotive OEMs.

With nearly four decades of experience, Trimble Inc. has been a leader in precise positioning systems for passenger cars. The company has provided its RTX technology for GNSS/GPS correction to General Motors for the Super Cruise hands-free highway driving system since 2018 and more recently for the hands-off freeway driving capabilities of Nissan’s ProPILOT Assist 2.0 on the 2023 Ariya electric SUV.

At Informa’s AutoTech event in Novi, MI, last month, we caught up with Marcus McCarthy, Director, of Autonomous Navigation Solutions, for Trimble’s on-road division, to discuss the latest trends and challenges for passenger-car positioning.

The company’s GNSS chips are used extensively in agriculture and construction applications for which the value of positioning is higher and tied into a business process. That is not the case for the passenger car industry, which tends to use comparatively low-end GNSS receivers from other suppliers with one or two frequencies and a limited number of channels—all for cost reasons, according to McCarthy.

For passenger cars, the company avoids hardware but provides positioning-engine software that makes the best use of the data stream to and from GNSS receiver chips. Its solution improves the average precision from roughly 3-10 m to better than 20 cm in open skies, which makes a big difference in the targeted car applications, he said. “The challenge for us over the last number of years has been to make those inexpensive receivers as accurate as possible” with software.

The company’s positioning engine does this by outputting position, time, and orientation data, which are fused with data from precision maps and sensors like cameras or lidars. If data from those sources “line up, within reason,” then the system is deemed safe and can be used for driving, he said. If they’re not, that’s a risky situation, and so the system disengages.

“For a lane that is 3 m wide, a tolerance within that 20 cm is generally going to be good enough,” he said, for Trimble’s systems used in SAE Level 2 and 3 automated driving systems. However, he says that higher levels of autonomy may need greater precision—in the 10-cm range.

“We already have R&D systems that are there,” McCarthy said. “We will get there with this inexpensive [GNSS receiver] technology.”

However, he says that error estimation is even more important than precision at higher autonomy levels.

“When we output a position, we also output an estimate of error with that position,” he explained. “That estimate of error, in my mind, is more important than the precision of the position because it tells the system whether it can use the position data or not. It’s kind of a black-and-white thing when it comes to saving lives.”

At what point is the data not usable? He put it into numbers.

“The target integrity risk of 10-7, which is one failure in 1244 years of continuous operation,” said McCarthy. “When we get to Level 4, that’s the standard [at which] we’re operating. I’m not going to trust my family in a vehicle if it’s not operating at that level.”

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The industry is innovating in GNSS, IMU and HD mapping technology, but more work is needed to develop higher performance, lower cost applications that enable instant, extremely accurate positioning at the centimeter level or better for lane-level navigation.

Advanced driving assistance systems (ADASs) and higher-level autonomous vehicle (AV) technology will require a fusion of data from an increasingly sophisticated set of perception sensors as well as absolute position information for safe operation. While improvements to perception sensors such as LiDAR, camera and radar have received a lion’s share of the recent media focus, technology for more precise positioning from GNSS, inertial measurement units (IMU) and high-definition (HD) map modules is a crucial element in enabling better and higher levels of autonomy.

Analyst firm Strategy Analytics expects demand for automotive-grade location services to increase with the penetration of embedded navigation in mass market vehicles, growth in the ownership of electrified vehicles, mandates for ADAS including upcoming European Intelligent Speed Assistance regulations, and the emergence of automated driving capabilities.

While many vehicles already depend on GNSS positioning for navigation, functionality can be compromised when the satellite signal is unclear. In urban canyons where tall buildings obscure the signal, for example, it can be inaccurate or slow to reach the vehicle. Other areas might not have much reception at all or can be affected by factors such as bad weather.

As advanced driver assistance systems continue to evolve, these positioning challenges must be overcome. Eventually, for even higher levels of automated driving systems to safely navigate their way on highways and around obstacles, they will need instant, extremely accurate positioning—at the centimeter level or better for lane-level navigation.

Setting the GNSS Standard

Much of the positioning industry’s efforts are aimed at improving the accuracy of a standard GNSS signal. A margin of error of up to 25 ft (762 cm) is not suitable for vehicles that require more precise absolute information to maintain lane-level positioning.

A prime example of this effort to achieve better precision is Trimble’s pioneering work with General Motors. In 2017, the two companies began a collaboration to develop a reliable way to maintain in-lane positioning for GM’s Super Cruise, the world’s first true hands-free driver assistance system, with Trimble RTX, which is said to be the first precise-positioning correction service to log significant miles in a commercial autonomy driving system. The collaboration reached a significant milestone in October, marking 5 years and more than 34 million miles driven with Super Cruise engaged on GM vehicles.

The ADAS application uses Trimble RTX (Real-Time eXtended) technology to deliver high-GNSS accuracy corrections starting with the 2018 Cadillac CT6. The technology, capable of accuracy better than 3.8 cm, enables a vehicle to maintain its lane position in a variety of environments including inclement weather such as rain, snow and fog. Such conditions often challenge other sensors in a vehicle’s ADAS/AV technology stack.

“Trimble RTX has been in commercial use for more than 10 years and in 2018 was the first precise point positioning correction service to log miles in a commercial autonomous driving system,” said Patricia Boothe, Trimble’s senior vice president of autonomy.

Trimble’s RTX technology removes errors in GNSS satellite data broadcasts to improve location accuracy on roadways.

“Super Cruise is a life-changing technology, allowing customers to experience hands-free driving on compatible, mapped roads nationwide,” GM Chief Engineer, Super Cruise Mario Maiorana said.

Inertial Measurement Unit Innovations

Another key sensing component for automated driving is the IMU, which measures force, angular rate, and sometimes the orientation of an object using a combination of accelerometers, gyroscopes, and sometimes magnetometers. It plays an essential role in the sensor fusion process by adding an extra level of redundancy.

A notable example of how this technology can benefit automated driving is the recent collaboration of Panasonic Industry and Finland-based Sensible 4 Oy on a new IMU. The partners established a joint test project leveraging Sensible 4’s autonomous driving software and Panasonic Industry’s IMU.

“The IMU is employed to rectify the point cloud and thus impacts the accuracy of LiDAR data,” Sensible 4 Marketing Director Fredrik Forssell said. “Our software is expected to be ideally flexible and reliable to next-gen sensor hardware.”

The partners are conducting in-depth testing with the six-axis sensor from Panasonic Industry. Specialists from both companies are involved in an extensive evaluation period with plenty of tests and analyses. According to Munich-based Panasonic, an average lateral error of 7.9 cm in testing matched Sensible 4 requirements for Level 4 automated driving.

“This project is a special one to all of us,” said Ryosuke Toda, who’s with product marketing at Panasonic Industry. “We are deeply interested in sending out our new sensor to this freezing baptism by fire to Finland and learn more on its readiness to contribute to that new level of mobility that we all are eagerly waiting for.”

Sensible 4 believes it has solved a major obstacle in autonomous driving—changing weather. Its technology combines software and information from several sensors, enabling vehicles to operate in weather conditions including snow and fog. In August, the company released its first autonomous driving software platform called DAWN.

“The ability to conquer new ground stems from DAWN’s features,” Sensible 4 CEO Harri Santamala said. “It is capable of operating in all weather, in darkness, without the need for lane markings, and in the presence of ever-changing environmental obstacles and surroundings.”

IMUs for the Mass Market

Tewksbury, Mass., based ACEINNA is looking to take precise positioning to the next level with MEMS-based, open-source, inertial sensing systems that offer higher accuracy at a lower cost—enabling easy-to-use, centimeter-accurate navigation systems. Its sensor product family is based on anisotropic magneto resistive (AMR) technology that enables industry-leading accuracy, bandwidth and step response in a cost-effective single-chip form factor.

At the 2022 CES in Las Vegas, the company announced its INS401 high-performance inertial navigation system (INS) with an RTK-enabled dual-frequency GNSS receiver, triple-redundant inertial sensors, and positioning engine.

“The INS401 is our next step forward, delivering complex INS/RTK technology to mass markets with turnkey products,” said Wade Appelman, president and COO at ACEINNA. “Highly accurate INS solutions like these usually run 10 grand or more; we have sliced that to under $500.”

The new offering is designed for use in Level 2+ and higher ADAS and other high-volume applications. The INS401 provides centimeter-level accuracy, enhanced reliability and optimal performance during GNSS outages. The dead reckoning solution delivers strong performance in GNSS challenged urban environments.

“We are now extending our proven solutions to the entire range of autonomous vehicle applications, from SAE Level 2 to Level 5, and bringing complex INS/RTK technology to mass markets with our turnkey products starting with the INS401,” ACEINNA Vice President of Marketing Teoman Ustun said.

The INS401 is specifically developed for automotive applications using automotive-qualified components and is certified to the ASIL-B level of ISO 26262. It is small, compact and turnkey with a rugged aluminum housing and an included “Integrity Engine” that is said to guarantee zero performance failure. The triple-redundant IMU has 80-channel tracking and algorithms to enable position accuracy of just 2 cm at real-time kinematic (RTK) levels.

Mapping out HD GNSS

The team at mapping company Here Technologies thinks it has the ultimate solution for positioning in urban canyons, in bad weather, and in areas that might not have much GNSS reception at all. Calling upon its experience in mapping, its HD GNSS Positioning offering combines the use of satellite GNSS signals with visual information from sensors and digital maps via an electronic horizon to help position vehicles accurately no matter the environment.

“From safer driving to smarter trip planning, having precise positioning will redefine how we move in the future and take vehicles to the next level,” Here Technologies Senior Product Manager Tatiana Vyunova said during a webinar on mastering precise vehicle positioning for autonomous driving applications.

With automotive and enterprise-grade receivers, Here Technologies’ solution can achieve accuracy to within 10-20 cm globally. It works with any GNSS receiver, requires no additional hardware, is easy to use, and can be combined with Here Lanes and Live Maps. If lost on a multi-lane highway or faced with an obstacle, the combined services can safely reroute a vehicle to its destination—getting information to the vehicle in less than a second.

Equipped vehicles with Level 1 and 2 automated driving systems can be guided into the right lane. For Level 2+ systems, HD GNSS Positioning enables true hands-free driving, according to the company.

Fleets also can benefit from the HD GNSS solution. Key use cases for the more precise technology include off-street locations such as logistics centers, truck and van automated deliveries, and emergency response vehicles.

HD GNSS Positioning is just one of the latest innovations from Here Technologies, which has been recognized as the top ranked location platform by industry analysts at Strategy Analytics. The analyst firm noted that Here HD Live Map is integrated into the Mercedes-Benz Drive Pilot System, the first commercially available SAE Level-3 capable autonomous vehicles in the world.

Putting it all Together with Map Simulation

One of the major silicon and AI companies also has waded into the localization space with a multimodal mapping engine aimed at accelerating deployment of Level 3 and Level 4 autonomy.

At its GTC 2022 event in March, Nvidia launched a mapping platform that combines ground-truth and fleet-sourced map engines to achieve accuracy and scale. A part of its Drive end-to-end AV development environment, it serves as a foundational dataset for labeling, training, validation and 3D environment reconstruction for simulation.

At his keynote, Nvidia Founder and CEO Jensen Huang introduced Nvidia Drive Map, which combines the accuracy of DeepMap survey mapping with the freshness and scale of AI-based crowdsourced mapping. The company expects Drive Map to provide survey-level ground-truth mapping coverage to 500,000 km of roadway in North America, Europe and Asia by 2024.

Drive Map contains multiple localization layers of data from camera, radar and LiDAR sensors so that an AI driver can localize to each layer of the map independently, providing the diversity and redundancy required for the highest levels of autonomy.

The camera localization layer consists of map attributes such as lane dividers, road markings, road boundaries, traffic lights, signs and poles.

The radar localization layer is an aggregate point cloud of radar returns, which helps in poor lighting and poor weather conditions. Radar localization is also useful in suburban areas where typical map attributes aren’t available, enabling the AI driver to localize based on surrounding objects that generate a radar return.

The LiDAR voxel layer provides the most precise and reliable representation of the environment. It builds a 3D representation of the world at 5 cm resolution, accuracy impossible to achieve with cameras and radar.

The AI-based crowdsource engine gathers map updates from millions of cars, constantly uploading new data to the cloud as vehicles drive. The data is then aggregated, loaded to Nvidia Omniverse cloud, and used to update the map, providing fresh real-world over-the-air map updates within hours.

Omniverse maintains an Earth-scale representation of the digital twin that is continuously updated and expanded by survey map vehicles and millions of passenger vehicles. Using automated content generation tools built on Omniverse, the detailed map is converted into a drivable simulation environment that can be used with Nvidia’s Drive Sim.

“Drive Map and Drive Sim, with AI breakthroughs by Nvidia research,” Huang said, “showcase the power of Omniverse digital twins to advance the development of autonomous vehicles.”

The post More Precise Positioning Needed for Vehicle Autonomy appeared first on Inside GNSS - Global Navigation Satellite Systems Engineering, Policy, and Design.

Kodiak Robotics, Inc. has been on a bit of a roll lately, developing automated solutions for long-haul truck routes in the southern parts of the U.S.

The self-driving trucking company made a big announcement on that front in August, unveiling a partnership with Pilot Company, the largest travel center operator in North America, to develop autonomous truck services at Pilot and Flying J travel centers. 

The companies are creating an autonomous truck port in the Atlanta area to evaluate potential service offerings and explore scalable solutions. The possibilities include spaces to pick up and drop off autonomous trucking loads; conducting inspections; maintaining and refueling trucks; and the ability to transfer data for feature development and mapping. 

The partnership is significant for both Kodiak and the industry. It establishes players like Pilot and its travel centers as premier locations to facilitate the various services autonomous trucks will need when they’re in production and deployed commercially, Kodiak CEO Don Burnette said. In addition, the Pilot centers will be access points for transferring data.

The Pilot partnership is just the latest development in Kodiak’s accelerating growth phase in 2022, with significant expansion coming in its service footprint and partner network as well.

In July, the company announced a partnership with 10 Roads Express, a provider of time sensitive surface transportation for the U.S. Postal Service, expanding the company’s service to Florida. And earlier this year, Kodiak announced a new route between Dallas and Oklahoma City with CEVA Logistics and a route between Dallas and Atlanta with U.S. Xpress.

A Fourth-Generation Autonomous Truck

This commercial success is being driven in part by the leading-edge technology in Kodiak’s fourth-generation autonomous truck. The new generation is designed for improved autonomous system robustness, with greater fleet uptime, manufacturing and serviceability in mind—all of which are critical to scaling the technology quickly, safely and efficiently, according to the company.

“Complex and bulky systems that require an engineer to hand-build and hand-tune are expensive, unreliable and difficult to debug,” said Burnette, who co-founded the Mountain View, CA-based Kodiak Robotics with Paz Eshel. “We believe that reliability and scalability flow from simplicity, and the best hardware modifications should be barely visible. Our fourth-generation platform is designed for simple, scaled production, which means easy calibration, troubleshooting and maintenance for our partners.”

The truck features a modular and more discreet sensor suite in three locations—a slim-profile “center pod” on the front roof above the windshield and pods integrated into both sideview mirrors. This better-integrated sensor placement is said to vastly simplify sensor installation and maintenance while also increasing safety.

The autonomous driving system features Luminar’s Iris LiDAR, Hesai’s 360-degree scanning LiDARs for side- and rear-view detection, ZF’s Full Range Radar, and the Nvidia Drive platform for the AI brains.

The Kodiak Vision perception system considers every sensor—including LiDAR, camera and radar—as primary, according to the company. All three sensors are purpose-built to meet the needs of autonomous trucks, which must “see” long-range in a variety of weather conditions to safely operate at highway speeds.

The system fuses information from the sensors and considers the relative strengths and weaknesses of each type. It incorporates extra redundancies and cross-validates data, adding another layer of safety to the self-driving system.

The patent-pending mirror pods—which will start with one Hesai LiDAR, two long-range 4D radars and three cameras—don’t require specialized sensor calibration. Rather than replacing a sensor in need of maintenance, a mechanic can replace the mirror pod in minutes. This single point of integration will allow for maintenance and serviceability at scale.

To make sense of all the data, the trucks will feature Nvidia Drive Orin, once available, as the supercomputing platform. With more than 250 TOPS (trillion operations per second) of compute performance, the platform is architected for safety and addresses systematic safety standards such as ISO 26262 ASIL-D (Automotive Safety Integrity Level-D). In the interim, Kodiak will use the current-generation Nvidia Drive AGX Pegasus to process data from cameras.

The Importance of PNT

When it comes to positioning, navigation and timing (PNT), Burnette said it “is definitely an area where we feel like Kodiak is really innovating within the space.” 

Within a mapping and localization framework, he said “ultimately the robot needs to answer the question, ‘Where am I?’ And once it knows where it is, then it needs to ask the question, ‘How do I drive from here?’ And then you just repeat those questions.” 

Historically, most companies have implemented high-definition (HD) maps of the environment using vehicle sensors to identify fine details like road texture surfaces, paint markings, tree trunks, buildings, sides of buildings, etc, Burnette said. 

“You name it, they put it in the map, and then they use that map to position themselves very finely in the real world,” he said. “And then they use an IMU [inertial measurement unit] to interpolate between those position-based preferences.”

His company diverges from the industry in this respect.

“We do it differently,” he said. “We have a very sparse mapping solution that only includes the road network—the lane connectivity information.”

For instance, the Kodiak system and lightweight Sparse map keep track of the number of lanes and their relation to each other and know where the exits and 
cloverleafs are. 

“From there, we localize based on what our sensors see relative to the lane markings that are relevant for driving, much the same way [that] humans do,” he said.

Kodiak engineers use an IMU to interpolate truck location as it moves down the road.

“Our positioning is very high fidelity in a lateral sense, but it’s not as high fidelity in a longitudinal sense,” Burnette said. “It just doesn’t matter if we’re one foot farther or one foot back on the road. As long as we’re close enough to be within the vicinity, we can identify key markers to tell us where we need to take our exits and where to expect other vehicles to be.”

That’s where GPS comes in.

“We have a very loose reliance on GPS just to bootstrap the system when we’re just getting started to kind of tell us where we are initially,” he said, “but also then to pull us gradually along longitudinally to maintain that semi accuracy.” 

Reliability is King

While performance and cost are important considerations for IMUs and GPS units—as well as the perception sensors—for autonomy, the key metric Kodiak developers are interested in is reliability.

“I think this is a bit of a surprise for most people, and it applies to all the sensors,” Burnette said. “At this stage, we’re not looking for improved performance. I think we have the performance we need from our sensors, compute and hardware that would be acceptable to launch this product safely. Cost is somewhat important, but what we really care about is reliability.”

The company has not announced the sources for its IMU and GPS unit, but wants suppliers capable of building solutions that can withstand the harsh environment trucks face day in and day out without breaking.

“If you can build a unit that will go hundreds of thousands of miles on the highway without breaking, that’s what we care about,” he said. “We care about reliability much more than any kind of fancy gizmo.”

The ability to withstand the typical shock/vibration is a top consideration, especially for IMUs, along with water ingress and temperature swings. 

“We drive in the heat of a Texas summer where it can get extremely hot, and it also must be able to work in the bitter cold,” he said. “So, temperature, shock and vibe, water, ingress, reliability—just general wear and tear—those are the types of things that we evaluate.”

Those evaluations continue as the company aims to integrate its self-driving software and hardware, the Kodiak Driver, into production customer trucks in early 2025. Kodiak Driver will operate self-driving fleets for a low per-mile subscription fee.

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At his keynote during the HxGN LIVE Global 2022 event in Las Vegas, Michael Ritter, president of Hexagon’s Autonomy & Positioning division, gave an overview of assured positioning and demonstrated how it provides the foundation for safe autonomy.

The world is on a fast track toward an autonomous future. From off-road tractors and rural transit systems to aerial vehicles and space exploration, automation will enhance safety, increase efficiency and improve people’s lives.

To make the autonomous future safe and secure, manufacturers and operators will need reliable, assured positioning, said Michael Ritter, president of Hexagon’s Autonomy & Positioning division. During his keynote at last month’s HxGN LIVE Global 2022 event in Las Vegas, he gave an overview of assured positioning and demonstrated how it provides the foundation for safe autonomy.

Assured positioning’s role in autonomy

Ritter explained how positioning technologies can enable the future of autonomy for high-precision positioning across industries including agriculture, mining and automotive.

“We’ve all heard about autonomy,” he said. “What’s one of the big problems there? It doesn’t always work as advertised.”

He mentioned Tesla’s AutoPilot as an example.

“In our industry, the non-consumer world, we can’t have that,” he added. “We need to have autonomy solutions that we can trust.”

One of the biggest factors in assured autonomy is accurate positioning data, Ritter said.

“If that is not a hundred percent waterproof, crystal clear, and protected from outside interference and cybersecurity threats, you can’t trust that position,” he said. “We have to know where we are at all times, and we cannot have that signal falsified.”

Building on the sustainability theme of the earlier keynote from Hexagon’s President and CEO, Ola Rollén, Ritter said a good way to become more sustainable is by taking operators out of the loop, especially for applications such as mining, material movement and agriculture “where operators have to do the same task over and over again… The more we can automate, the more we can protect their life and happiness.”

Autonomy challenges

While Ritter doesn’t think he’ll see the universal use of autonomous vehicles in passenger traffic during his lifetime “because legislation will be in the way,” he said applications in “off-road autonomy—construction, mining, material transportation and agriculture—[are] here today.”

Hexagon is working with many customers on semi-autonomous solutions for those applications.
“Those all take place in confined spaces that are controlled; legislation is not such a big problem,” he said. “This is happening right now. We don’t have to wait 10 [to] 20 years for that.”

However, a big safety challenge in expanding autonomy is anticipating all the corner cases, or “all the stuff that could happen once in a lifetime,” Ritter said. Those can be overcome by real-life testing, multiplying that with simulation “a hundred million times over,” and then going “back into real life” and performing “real, extreme testing.”

The breadth of Hexagon’s experience helps in this regard, as more extreme applications can benefit other, less-extreme use cases. Ritter gave an example of a fighter jet, which places extreme demands on acceleration, deceleration, GPS and inertial systems.

“If you survive [in those conditions], then odds are [systems] never will fail while seeding or spraying in an agricultural environment or having an autonomous loader somewhere in an ore-loading operation,” he said.

Real-world solutions

Hexagon has a lot of experience with autonomous systems, a fact most people don’t realize, Ritter said. For example, in the U.S. and Europe, Hexagon technology is the backbone of the SBAS (satellite-based augmentation system) that allows airplanes to better use GPS to operate autonomously.

“It’s in everyday use,” he said. “It’s mandated in certain airports, and it’s used by a lot of different aircraft.”

In 2020, Hexagon announced shipment of next-generation ground uplink station (GUS) signal generators in support of a U.S. Federal Aviation Administration (FAA) contract for its WAAS (Wide Area Augmentation System) navigation service.

Developed by the FAA for civil aviation, WAAS is a safety-critical navigation aid that provides integrity monitoring and differential corrections for all phases of flight. Along with GUS modernization, the contract includes ongoing engineering support services for the portfolio of Hexagon’s NovAtel ground reference receiver products deployed by the FAA.

Hexagon solutions have achieved success a little further up—in space—where that environment brings other big equipment challenges. One side of a vehicle facing the sun can get very hot, while just a few millimeters away on the shaded side it can be really cold.

“If you can master that, odds are you can master mining operations in Alaska and in the desert,” Ritter said of his company’s experience.

Space presents other engineering challenges, Ritter said. Signals from GPS satellites are very faint for earth-based applications.

In May, Hexagon’s NovAtel unit signed an MoU to collaborate with Xona Space Systems on its new Low Earth Orbit (LEO) constellation. The technology offers a new way of assuring PNT (positioning, navigation and timing) by providing stronger signals with satellites closer to the Earth and improved positioning accuracy with rapidly changing geometry.

Additional constellations and a larger number of available satellites improves visibility in cases where parts of the sky are obstructed by buildings and other obstacles. And as the threat of unintentional or malicious jamming and spoofing increases, it becomes important to consider alternative sources of PNT and resiliency methods.

Xona’s new constellation will transmit encrypted signals on two frequencies, both offering authentication, further building new levels of resilience against malicious interference. As an early adopter of Xona’s signals, NovAtel aims to demonstrate its continuing leadership in resilient assured PNT and “all source PNT” innovation.

Going more mainstream

While the universal use of autonomous vehicles in passenger traffic may be further off, Hexagon’s previous applications and experiences have allowed the company to expand to more mainstream applications, Ritter said.

One of those is an automotive GNSS positioning module designed to enable ADAS (advanced driver assistance systems) and autonomy at scale. Hexagon’s NovAtel has introduced the PIM222A, part of a new family of automotive GNSS positioning products that harness the unit’s experience delivering precise positioning in the most demanding applications for mass deployment in ADAS applications and autonomous vehicles.

Built with automotive-qualified hardware in a package that is easy to integrate, the PIM222A leverages SPAN technology from NovAtel to provide accurate position data in urban environments that challenge GNSS availability. Deeply coupled GNSS receivers and inertial measurement units (IMUs) ensure continuous availability of position, velocity and attitude, even when satellite signals are briefly blocked.

Created in collaboration with STMicroelectronics, the PIM222A module’s receiver design can be applied to low-, medium- and high-production volumes while retaining an array of feature options such as multi-frequency, multi-constellation, RTK and dual-antenna precision. The degree of slow-speed and initialization performance is maximized with the dual antenna feature, enabling the best possible positioning performance in all ADAS and autonomous driving situations.

Development kits for the PIM222A are available now for integrators in need of a positioning essentials solution for low- to high-quantity applications.

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