Hesai Technology (HSAI) and Inertial Labs have announced a multi-year technology partnership agreement for LiDAR sensors to provide perception and navigation capabilities for autonomous marine, land, and aerial-based robotics systems. Inertial Labs, a global leader in mobile robotics navigation systems and inertial measurement units, has selected Hesai’s sensors to enable its navigation systems for robotics systems to operate autonomously and safely.
Hesai’s LiDAR sensor solutions enable robotics systems to operate autonomously and safely without human intervention. The sensors provide real-time 3D point cloud data for localization, obstacle detection, and path planning. Hesai’s low-power sensors support autonomous mobile systems in various outdoor environmental conditions, including precipitation from rain, snow, and fog. The sensors are also unaffected by varying lighting conditions and can operate in daytime and nighttime.
“Inertial Labs is a company with a rich history in hardware engineering. Our mission is to develop cutting-edge solutions that drive the adoption of advanced sensor-fusion navigation and perception technologies at more affordable costs. Our unwavering commitment to quality is evident in our products, which are designed to meet the highest performance and reliability standards. At Inertial Labs, product excellence is always our top priority. To ensure the quality and accuracy of our products, we conduct exhaustive testing in our labs and gather feedback from customers worldwide. Our research has led us to conclude that Hesai LiDAR sensors are the ideal choice for achieving highly accurate and reliable 3D measurements,” stated Inertial Labs CEO Jamie Marraccini.
Inertial Labs has a rich history in hardware engineering and is dedicated to developing cutting-edge cost-effective navigation and perception solutions using advanced sensor-fusion technologies. The company’s products are rigorously tested and receive customer feedback worldwide, ensuring the highest quality and performance. Based on its research, Inertial Labs has concluded that Hesai LiDAR sensors are optimal for achieving accurate and reliable 3D measurements.
“Inertial Labs’ navigation and Inertial Measurement Units (IMUs) provide seamlessly integrated heading and ego-motion data to the LiDAR data stream. With this fused data stream, customer’s robotic systems can expertly navigate a variety of Operational Design Domains (ODDs) from the land, sea, and air,” stated Frank Bertini, Director of Technical Marketing at Inertial Labs.
The technology partnership agreement between Hesai Technology (HSAI) and Inertial Labs for LiDAR sensors is expected to bring innovative LiDAR solutions to the market that will help advance the unmanned aerial systems and drone industry forward.
As tactical UAVs come of age, inertial technology’s ability to endure GPS outages while providing reasonable accuracy at high update rates keeps it as the backbone of UAV sensor systems. Coupling inertial with M-code, anti-jam antennas and vision in the autonomous arsenal can make the sum of parts a very robust solution.
In defense applications, as military users look to achieve new capabilities with unmanned autonomous aircraft, three main areas come into sharp focus: vertical takeoff and landing (VTOL), launching of UAVs from other flying aircraft, and overcoming jamming in GNSS-denied environments. Coupling a high-performance inertial measurement unit (IMU) with other sensing and navigation technologies on a UAV into a highly capable inertial navigation system (INS) can bring a solution to overcome each of these obstacles.
“The GNSS-aided INS is the backbone for these types of systems,” said Jeremy J. Davis, Ph.D., Director of Engineering, VectorNav. “It can ride through GPS outages and do it at high update rates, and still be reasonably accurate. Beyond that, different enabling technologies like anti-jam M-code and vision can merge with it and provide a more robust solution. That is a space of heavy activity right now, and we’re working on solutions internally and with partners that meet these types of requirements and do so seamlessly.”
VTOL, air launch and GNSS spoofing and jamming are all challenging UAV problems that haven’t been fully solved yet, but state-of-the-art companies are designing next-generation vehicles that will take them on.
VTOL
The ability to launch and retrieve a UAV without the expense, exposure and advance logistics required by a runway presents obvious tactical advantages to mobile warfighters. Rotorcraft such as helicopters and quad-rotors require only a small takeoff and landing zone, but they are inefficient compared to fixed-wing UAVs, and have dramatically lower range, payload capacity, and dwell time. Catapult-launched fixed-wing UAVs solve half the problem, but still require a runway for recovery—and catapults are cumbersome to transport.
VTOL aircraft avoid all these disadvantage and bring the cruise and payload advantages of fixed-wing UAVs. There are broadly three approaches to VTOL:
• a hybrid rotorcraft and fixed-wing vehicle, also known as a quadplane, with a set of vertical propellers for takeoff and landing and one or more horizontal props for cruising;
• a tiltrotor vehicle, using the same propellers are used for vertical and horizontal propulsion, rotating them in mid-air relative to the vehicle;
• tail-sitter UAVs which takeoff and land on their tails, like a rocket, but cruise horizontally, accomplishing both types of flight with one fixed set of propellers.
All types of VTOL craft require more from their navigation systems than other types of UAVs. “Takeoff and landing are the most dangerous, riskiest elements of flight for all types of aircrafts,” said Davis. “When you’ve got these VTOL aircraft that are reimagining how to do takeoff and landing, it presents obvious inherent risks. You have to make sure you’ve got all your I’s dotted and T’s crossed.” The introduction of a major in-flight transition at a mission’s beginning and end—quad-planes switch from one set of props to another, tiltrotors rotate their entire propulsion system, and tailsitters switch from getting lift from their wings to solely from their propellers/rotors—presents several challenges for the navigation system. VectorNav has been working through these problems with customers over the last five years and brings this experience to bear on what is rapidly becoming the next frontier for tactical military UAVs. The requirements on the navigation system include:
• Absolute reliability.
Other control dynamics must be carefully monitored and managed; there’s no room to worry whether the navigation system can be trusted through the transition. For tail-sitters, this also means algorithms that avoid gimbal lock when rotating 90 degrees in pitch during the transition.
• Slow and fast operation.
To track heading, hovering aircraft typically rely on a GNSS compass: two GNSS antennas a fixed distance apart. Fixed-wing aircraft use an INS-generated heading following a dynamic alignment process, correlating the motion measured by the GNSS and the IMU. For a VTOL aircraft, both techniques are critical for different phases of flight, and the handover between the two must be flawless to avoid compounding problems during vertical-horizontal flight switch. VectorNav dual-antenna GNSS systems like the VN-300 and VN-310 smoothly transition between whichever heading source is the most accurate at any given time.
• Landing.
Some of the most advanced systems in development must land on moving platforms such as ships or trucks. This requires extremely high precision. An RTK-enabled GNSS receiver, like those found on the VectorNav Tactical Series units, can provide centimeter-level relative positioning at high update rates.
AIR-LAUNCHED
One way of multiplying the range of a UAV, while also avoiding the downsides of a runway, is to launch it from a much larger air-craft already inflight. These UAVs are often tube-launched, with wings that unfold/unfurl in the first seconds of flight as it emerges from the host aircraft already at top cruising speeds. The transition phase for these UAVs is quite dramatic.
All of this places severe strains on the navigation system: rotations of a few 1,000 degrees per second in the airstream and high acceleration rates. It’s a wild, rolling ride during which GNSS is typically lost, whether due to the high G’s, the abrupt switch from the host’s GNSS antenna to the UAV’s antenna, or the fact that the UAV antenna may not point reliably skyward until stable flight is reached.
Air-launched UAVs must also cope with buffeting from the wake of the launching aircraft. Shocks are high and the accelerations and angular rates experienced immediately upon deployment are extreme until the UAV’s wings unfurl and can stabilize the craft. Stabilization itself it a critical achievement for the navigation system to control, to catch itself before falling headlong downwards.
It’s an exciting handful of seconds. All of this requires the navigation system to run in a pure inertial navigation mode, tracking through high g-loading and higher angular rates. As with the VTOL aircraft, this period right after launch is critical to mission success. Maintaining the level of attitude accuracies that VectorNav has achieved under these circumstances is a non-trivial problem.
The UAV’s navigation system must also handle a process known as transfer alignment, wherein it initializes while still onboard the host aircraft. Depending on the system, this can be handled in different ways. The host aircraft’s navigation system can provide a full navigation solution just prior to launch, from which the UAV INS initializes, though this requires tight integration between the avionics systems. Or, the UAV’s navigation system can be enabled for a short period (30 seconds to several minutes) prior to launch, with GNSS signals provided from an antenna mounted on the host aircraft. This allows the GNSS/INS to fully initialize itself, and then switch its own internal antenna is made after launch. This can be much more robust and can allow lower-risk integration with the host aircraft.
“This is the secret sauce part of the deal,” said Davis. “Getting our filters going and tracking pre-launch, then somehow take this filter that’s working in the rather benign conditions pre-launch, and make sure that it continues to work after being subjected to a really high-G event with crazy tumbling and more.”
GPS-CHALLENGED ENVIRONMENTS
Having to operate with a GNSS signal that may be spurious, or without GNSS altogeth- er, poses a whole new set of problems for a tactical UAV. An active spoofer or jammer in operational theater area interferes with the UAV’s onboard GNSS receiver, and the right mitigation technologies must come into play to maintain accurate tracking in these extremely difficult environments.
GPS M-code receivers now being gradually deployed throughout the US military and those of its allies replace the SAASM (Selective Availability Anti-Spoofing Module) receivers that previously thwarted spoofing attempts. M-code technology also takes advantage of new, more powerful signals from the latest GPS satellites to counter jamming as well. VectorNav’s Tactical Series of INS systems have full support for interfacing with those new types of receivers.
To complete spoofing mitigation, anti-jam or controlled reception pattern antennas (CRPAs) consist of multiple elements, allowing them null signals coming from directions likely to contain spoofers jammers while amplifying signals from known satellite directions.
The combination of a tactical grade IMU with an M-code GNSS receiver and an anti-jam antenna provides a navigation solution robust to common GNSS-challenged (spoofed) environments.
Short-duration GNSS outages, lasting seconds to a few minutes can be readily handled by VectorNav’s tactical grade GNSS/INS sensors like the VN-210, relying on pure integration of the accelerations and angular rates reported by the inertial sensors to provide navigation when GNSS is unavailable.
“Because we have good IMUs in our tactical series,” said Jakub Maslikowski, Director, Sales and Marketing, VectorNav Technologies, “we can handle GPS chal- lenged conditions for limited periods of time. To the extent that somebody does manage to jam you briefly, the inertial sensors will carry you through.”
GPS-DENIED
Increasingly, continued operation in GNSS-challenged environments isn’t enough: UAVs must also operate in fully GNSS-denied situations, where powerful enemy jammers attempt to control the field. Larger systems, including manned aircraft, can rely solely on a navigation-grade INS, which drifts on the order of kilometers per hour. But a navigation-grade INS is far too large and expensive for most UAV applications.
Achieving accurate, reliable navigation without either GNSS or a navigation-grade INS is an area of active R&D at VectorNav involving many different sensing technologies.
Electro-optical and/or infrared (EOIR) camera systems have come into increasing play for GNSS-denied navigation. Image-processing software processes each image to identify unique features that it would recognize again in the next image taken, a process known as feature matching.
If a UAS has pictures of the area taken prior to the mission, by satellites or other overflight, this enables a map-matching approach: matching the features from the real-time images to the stored image map for localization, thus determining UAV position. This can supply high accuracy but requires significant advance preparation. It only works over an already-known area, flying a predefined path at a predetermined time of day, since shadows and lighting differences can impact the accuracy of map- or image-matching.
When a map isn’t available, vision-based navigation systems can create their own map as they go, using simultaneous localization and mapping (SLAM). The drawback of SLAM is that the map will be imperfect, and those imperfections grow over time. SLAM position errors drift as a function of distance traveled.
All vision-based systems struggle, natural- ly, in limited visibility such as clouds or fog. Active sensing systems like radar or LiDAR, which emits laser pulses to produce a 3D map, can replace or augment vision systems. However, active sensing brings the downside of potentially revealing one’s own position to the enemy through the emitted signals.
Finally, all of these technologies fail when the environment, such as large bodies of water or a sandy desert, contains no distinct features.
As an alternative to outfitting smaller UAVs with complex GNSS-denied navigation systems, an aircraft “buddy system” can involve multiple UAVs operating in the vicinity of a larger aircraft equipped with a navigation-grade INS. The large, heavy and expensive navigation-grade INS can fly for hours without drifting more than a couple kilometers. This then shares its location with the smaller UAVs through various combinations of radio links, visual markers and other techniques.
Clearly, there is no one solution that counters GNSS signal jamming under all conditions. A robust, reliable and versatile system must combine several technologies, playing the strengths of some off the weaknesses of others. This is where a highly adaptable and flexible INS system with a tactical-grade IMU can provide tremendous value, functioning as the linkage of a multi-sensor system. VectorNav has been working for years with some of the most advanced companies exploring each of these technologies and integrating them with algorithms for a powerful anti-jamming solution.
CONCLUSION
VTOL and air-launched UAVs will dramatically alter the landscape of UAS for military use. Their unique flight profiles, however, require sophisticated navigation systems that go beyond traditional INS capability. VectorNav is taking the lead in integrating the latest navigation technologies to handle these demanding situations.
Making these systems robust to GPS- denied conditions means integrating the latest PNT technologies, from M-Code to anti-jam to vision. Working closely with a partner like VectorNav that can integrate with these various complementary technologies can provide tremendous value and save considerable engineering resources. Go to www. vectornav.com to begin the process.
Selecting GNSS and Inertial for Intelligence, Surveillance and Reconnaissance
Inertial technology coupled with GPS/GNSS plays a critical role in the fast-growing field of intelligence, surveillance and reconnaissance (ISR) applications. This article covers the key factors to consider in selecting the best GPS/inertial integration for your particular ISR job.
With any tool, you need the right one for the job, and inertial technology comes in many forms, with many different capabilities. If optimally selected, your GNSS-aided Inertial Navigation System (GNSS/INS) will form the linchpin in positioning your ISR sensors for best results. Keys to consider are differences in errors that will inevitably be encountered: determining, relative to the desired level of performance, which errors are tolerable and which are not. This is called the error budget and is the first thing to review with knowledgable equipment suppliers.
ISR technology finds increasing application in military, law enforcement, search and rescue, border patrol, disaster response and many other fields. In most cases, an airborne camera gathers data key to the operation, to locate, map and geo-reference points of interest.
Typically, an electro-optical and/or infrared (EO/IR) camera is mounted on a gimbal, a pivoted support that rotates the camera around a single or a double axis. Gimballed systems are common on UAVs, aircraft and marine vessels. They enable pointing the sensor payload toward objects of interest, independent of the platform’s attitude or movement. That independent motion also allows for stabilization (or regulation), decoupling the high-frequency motion and vibrations of the platform or vehicle from those of the payload.
For a variety of reasons, gimballed payloads incorporate their own position and attitude (heading/yaw, pitch and roll) sensing in most applications, rather than relying on the platform’s GNSS/INS. The aircraft’s navigation system may not be accurate enough for geo-referencing objects seen from as far as 10,000 meters. In some cases, the aircraft’s navigation system may be mission-critical and thus unavailable to the ISR sensors. Finally, flexing of the aircraft introduces errors since the platform’s INS is typically mounted near the center of mass of the vehicle and not co-located with the gimbal.
POSITIONING THE SENSORS
For most gimbal-pointing applications including geo-referencing, the gimbal control system requires position data, which precludes a pure Inertial Measurement Unit (IMU) or Attitude Heading Reference System (AHRS) solution; it requires a GNSS-aided option. Even for applications where positioning is not required, the high-accuracy pointing requirements during dynamic motion mean that the degraded performance an AHRS suffers during such dynamics is unacceptable; again, a GNSS-aided solution is needed.
A GNSS/INS system is composed of inertial sensors (which come in a variety of grades), a high-sensitivity GNSS receiver, and Kalman filtering and algorithms. Measurements from the GNSS receiver are coupled with the inertial measurements to provide position, velocity, and attitude estimates of higher accuracy and better dynamic performance than a standalone GNSS, INS or IMU/AHRS can provide.
A GNSS/INS system typically includes a 3-axis gyroscope, a 3-axis accelerometer, a GNSS receiver, and sometimes a 3-axis magnetometer to determine a navigation solution. Each of these sensors contribute different measurements—and different potential errors—to the GNSS/INS system.
Combining GNSS and INS enables them to complement each other, overcoming some of the limitations they each face as standalone systems. A few issues remain to be addressed in an integrated GNSS/INS system.
This article covers how to select the right GNSS/inertial unit combination for a specific application, and how to integrate that into the full range of pointing, sensor, and geo-referencing systems.
DO I NEED A GNSS COMPASS?
A GNSS/INS provides accurate data under dynamic conditions, generally for platforms moving at 5 meters/second (roughly 11 mph) or faster. A single-antenna GNSS component is generally reliable for this type of application, being able to track heading through a process called dynamic alignment. This correlates accelerometer measurements with GNSS measurements to track heading in the presence of horizontal acceleration. This is not the same as course-over-ground of a GNSS system, but is rather the true heading of the system.
Since it relies on dynamic alignment, a single-antenna GNSS/INS will lose its ability to accurately track heading in applications where the platform is stationary or moving slower than 5 meters/second, such as helicopters, rotor UAVs, or marine vessels. Even large aircraft that endure long periods of straight and level flight may find that their attitude solution wanders during such periods of low dynamics. In these scenarios, a GNSS/INS with integrated GNSS-Compass is preferred.
A GNSS-Compass is a system composed of two GPS receivers connected to two external GNSS antennas some fixed distance apart. Differential GNSS calculations are used to determine the relative position of the two GNSS antennas to millimeter-level accuracy to measure the heading of the system. The heading accuracy of this GNSS-Compass is inversely proportional to the separation distance between the antennas.
VectorNav’s VN-300 and VN-310 GNSS/INS products are examples of dual antenna GNSS/INS systems. Advanced GNSS/INS systems with integrated GNSS-Compasses such as the VN-300 and VN-310 can automatically transition between the dual-antenna heading solution and dynamic alignment to output the most accurate heading, depending on real-time motion of the systems.
STANDARD GNSS VS RTK AND INDUSTRIAL VS TACTICAL GRADE INS
Inertial sensors come in different grades, depending on their gyroscope-induced error budgets. ISR applications typically require either industrial or tactical grade IMUs. There can be an order of magnitude difference between them.
RTK involves use of a base station on the ground in addition to the GPS/GNSS receiver onboard the aircraft, and yields a higher degree of positioning accuracy. RTK has its limitations, however: extra size, weight and power, cost, additional hardware with base station, range to base station, and so on.
Figures 1 and 2 show the image overlay uncertainties contributions from the GNSS/INS, depending on industrial-grade vs tactical-grade inertial performance, and standard L1-only GNSS vs external RTK GNSS positioning.
Since heading accuracy is much worse than pitch/roll accuracy, Figures 1 and 2 also show the uncertainties based on whether the gimballed camera is generally downward-pointing (yaw errors negligible) or horizontal (yaw errors dominate). At short ranges (<100m), the GNSS accuracy dominates the system accuracy, whereas at long ranges (>1000m) the INS performance is determinative.
ISR SYSTEM ERROR BUDGET
The estimated pointing solution of the gimbal (˜PG) can be found by taking the offset of the feature in the camera (xˆ, yˆ, fˆ) and rotating it to a North-East-Down (NED) coordinate frame using an estimated coordinate frame transformation matrix (C) and multiplying it by the slant range (L) and adding it to the position of the aircraft (˜PA) as shown in Equation 1.
Each term in the equations is subject to different errors from different sensors. The error budget determines the contribution of all data sources—each sensor has an inherent margin of accuracy—that affect the acquired data quality, to check if the degree of uncertainty in the measurement solution meets the minimum job specifications.
An error budget quantifies all of the sources of error in a system, and accumulates them into a total system performance. By understanding how certain sources of error affect the ISR system, as well as the magnitude of those errors, total system performance can be improved through smarter design choices and error mitigation techniques.
It is useful to split errors into NED coordinate frame errors and errors orthogonal to the slant range. Direct errors in position are usually referenced in an NED coordinate frame, while errors related to attitude can be represented as perpendicular to the slant range.
For all errors related to attitude (∈ [°]), the error in position (σ¯[m]) can be calculated as a function of some distance (d) as shown in Equation 2. This can be used to find the error perpendicular to the slant range.
GNSS/INS PERFORMANCE IMPACT
A GNSS/INS introduces a measure of error into the positioning and heading solutions for the sensor suite and its produced data. The error budget from GNSS/INS uncertainty can be split into GNSS/INS position error and GNSS/INS attitude errors.
Position errors largely reflect errors in the GNSS solution. These are caused by satellite orbit data inaccuracies, satellite clocks, receiver noise, ionospheric delay, tropospheric delay, and multipath, or reflected signals. GNSS horizontal and vertical position errors translate directly to those same errors in the pointing solution.
Meanwhile, attitude errors are largely determined by the INS. Inertial sensors are subject to several common error sources such as bias, noise density, scale factor, misalignments, temperature dependencies, and gyro g-sensitivity.
The contribution to the error budget from the attitude uncertainty can be calculated by finding the error perpendicular to the slant range. The exact translation from roll/pitch/yaw to position errors in the slant range frame (dependent on gimbal look-angle, α) can be found using Equation 2 and the values in Table 1.
Multiple sources of INS error must be accounted for when determining how much error is acceptable for an accurate navigation solution (see Figure 3).Although not described in detail here, these need to be accounted for by professional guidance in manufacturing and installing a GNSS/INS on your platform. VectorNav can provide such guidance.
OTHER ERROR SOURCES
In addition to the error contributions from the GNSS/INS, a system designer or integrator must consider a variety of other terms in the error budget, including misalignments, timing errors, and camera distortions.
Misalignments between the navigation system and the imager electronics sometimes exceed the attitude errors of the GNSS/INS system itself, and their effect can be characterized similarly attitude errors from GNSS/INS, using Equation 2 and Table 1.
Time synchronization between the EO/IR system and the GNSS/INS is also critical. Any errors in timing will be multiplied by the linear and angular velocities of the gimbal to create additional position and attitude errors.
To compensate for misalignment and timing errors, the system should be calibrated on a part-by-part basis to determine the fixed misalignment offset by comparing the measured values of the system to some independent source of truth. We recommend that this calibration take place in a benchtop testing environment during manufacturing to prevent the introduction of other error sources during the calibration.
And of course, the EO/IR system itself will have errors that must be accounted for in the error budget, ranging from intrinsic parameters that can be calibrated, like lens distortions and focal length, to limitations on accuracy due to the resolution of the imager and the performance of the image-processing algorithms.
EXAMPLE
As an example of an ISR application we will look at the case where a surveying camera is mounted to a plane. Once an image is taken, a point is georeferenced using a flat and level digital elevation model (DEM) combined with gimbal attitude and position. Often, ISR applications call for mapping a point or a feature on an image to a DEM tied to a global coordinate frame (see Figure 4). This can be done by iteratively trying to find a slant range (L) such that the pointing solution aligns with the DEM.
Because we know that our georeferenced point lies on a 2D DEM the error only exists in two dimensions. In this case a plane will be traveling at 50m/s due North at a height of 1000m. Since the error budget of many of the error sources on the gimbal depend on slant range, the example will be assessed with the gimbal pointed 60 degrees directly in front of the vehicle with a theoretical slant range of 2000m. For comparing error the same configuration, GNSS/INS system, and Camera should all be used.
In a flat DEM the error budget from horizontal GNSS/INS uncertainty directly comes from the GNSS horizontal position uncertainty in an NED coordinate frame. For standard GNSS this gives an error of 2m in the North and East axis. The contribution from the GNSS altitude uncertainty gets projected onto the DEM as a function of the gimbal tilt angle. The position error contribution can be reduced to centimeter level by using RTK.
Figure 5 shows the overall resulting error budget, using all these calculations, for different combinations of two types of inertial sensors, industrial and tactical, and two types of GPS/GNSS technology, with and without real-time kinematic (RTK).
CONCLUSION
We have outlined the critical factors to consider in selecting an integration of inertial and GNSS equipment for your ISR application. Clearly, the calculations are complex and the results call for careful interpretation! And, every application has different requirements; aerial surveys conducted at 100 meters altitude by a small UAV rotorcraft call for a different solution than those done from 10,000 feet by a piloted airplane. VectorNav professionals can guide you through the selection and equally important installation process for your specific job. Go to www.vectornav.com to begin the process.
SBG Systems announced the tactical-grade Pulse-40 inertial measurement unit (IMU) in a miniaturized size for precision and robustness under harsh conditions, with an excellent size, weight, power and cost (SWAP-C) rating for its category.
The Pulse-40 is a 6 degrees-of-freedom, tactical grade IMU integrating micro-electromechanical systems (MEMS) three-axes accelerometers and gyroscopes in a unique redundant design that permits reducing system size while pushing performance level to the maximum.
Among the performance specifications, the Pulse-40 features excellent gyro and accelerometer bias instability of 0.8°/h and 6µg respectively, enabling long dead reckoning and maintaining excellent heading performance.
Thanks to a rigorous selection of sensors featuring extremely low vibration rectification error (VRE), the Pulse-40 can sustain high-vibration environments, up to 10g RMS. Data reliability during operation is also ensured by the embedded continuous built-in-test, enabled by redundant sensor integration. This functionality is a key parameter for critical applications. The Pulse-40 requires no periodic maintenance. An intensive qualification process including accelerated aging guarantees that the sensor behavior is stable over time.
The Pulse-40 comes with a 2-year warranty. It is export license-free and ITAR-free.
SBG Systems has a long-term history of designing quality MEMS-based inertial navigation systems (INS). Extensive research in signal processing, micro-electronics, calibration algorithms, and sensor qualification have won the company a reputation for accuracy and reliability since 2007. Its sensor calibration and validation tools, initially based on a single axis motion simulator with a temperature chamber, have evolved over the years and are now based on 100% automated, multi-axis motion simulators with temperature chambers. The high level of automation mitigates human error risk and ensures that all the delivered products meet their specifications.
SBG Systems is an ISO 9001:2015 certified company.
Inertial Labs, a developer and supplier of orientation, inertial navigation, and optically enhanced sensor modules, has acquired MEMSENSE, a developer of inertial measurement units.
The combined company expects to introduce new technologies for autonomous vehicles, GPS-denied navigation, industrial machines, and aerospace & defense. The combination will produce the following benefits, according to the companies
Increased production capabilities of up to 50,000 units annually in order to meet the needs of larger aerospace and defense contracts for guidance and navigation applications;
Low-cost, consumer-grade IMUs; ruggedized industrial-grade models; affordable tactical-grade inertial measurement units (IMUs) and with near-fiber optic gyro (FOG) level of performance (0.1 deg/h bias instability);
A larger range of devices for unmanned ground vehicles (UGV); unmanned aerial vehicles (UAV); autonomous and automated ground vehicles (AGV);
Expanded R&D efforts to accelerate delivery of IMUs for stabilization applications like electro-optical systems, pan and tilt platforms, and remote weapon stations (RWS);
New IMU models with improved performance will increase capabilities of the Inertial Labs GPS-aided inertial navigation systems (INS), wave sensors, motion reference units (MRU) and attitude heading reference systems (AHRS);
To complete development of new high-performance systems including a MEMS-based gyro-compasses (3 MILS Azimuth and 1 MIL Elevation accuracy).
We take a close-up look at inertial measurement and inertial navigation in autonomous cargo transport. High standards for technology in the lab and in the factory are all very fine, but what matters most is how it works in industrial application. This free webinar also examines oil and gas pipeline inspection and stabilization of optical camera platforms.
Three experts in the application of inertial technology discuss the challenges they confront daily in their respective fields, and how they achieve rock-solid success with gyroscopes from KVH.
In the fast-deveoping field of drone delivery, an exciting start-up is bringing same-day shipping to everyone in the world: the first autonomous drone capable of delivering 300 to 500 pounds of cargo over a 300-mile range, with no need for an airport or electric charging station. Elroy Air recently announced a partnership with NASA to accelerate the integration of autonomous cargo aircraft in the U.S. Its current Chaparral model boasts a hybrid-electric powertrain and the ability for autonomous cargo loading and unloading, allowing a single pilot to operate a fleet of 10–50 UAVs from a remote location. Again, the inertial sensor proves essential to mission accomplished.
In the inspection of oil and gas pipelines, gyroscopes within a “pig” that travels the internal length of the pipeline, from 900 meters to 900 kilometers, give the centerline coordinates as well as measurement of any bending strain on the conduit. Onstream Pipeline Inspection Services looks for integrity threats such as corrosion, deformation and strain events. Inertial mapping units are used for calculation of bend strain and to give positional information to be able to locate the other threats correctly. Their main challenges are size, low power consumption, inertial accuracy, gyro rate and ITAR restrictions.
For sight optimization of optical payloads on air, land and sea, Gyro Stabilized Systems designed an open architecture platform that is versatile and interchangeable, adapting to different gimbals that may carry infrared, corona cameras, radiometric sensors, gas detection, still cameras, broadcast cameras, and cinema production with long lenses. Their byword is diversity, with the ability ability to customize and quickly switch out sensor payloads. The presentation includes a quick gimbal tutorial, what to look at when selecting sensors, the caveats and tradeoffs in building 5-axis and 6-axis systems with innovative steer and control modes. Results of payload stabilization in helicopters and other moving platforms demonstrate that at the heart of success is a really good inertial sensor.
Buddy designs the navigation apparatus for this autonomous aerial cargo aircraft systems developer. He has a Ph.D. in autonomy and artificial intelligence from the Massachusetts Institute ofTechnology and is a licensed private pilot.
Stephen Westwood Senior Director, Engineering and Technology Onstream Pipeline Inspection Services
Stephen brings over twenty years of design experience in In Line Inspection tools. He holds a PhD inExperimental Magnetism and BSc in Experimental Physics. Stephen’s expansive knowledge of pipeline inspection tool development includes algorithm development and magnetic design of In LineInspection tools. Previous roles have seen Stephen building and leading multi-disciplinary groups in new product development throughout his career. Stephen’s industry knowledge, experience and unparalleled reputation will be a driving factor in Onstream’s continued development and growth within the In Line Inspection industry.
Michael Lewis Software Engineering Manager Gyro-Stabilized Systems
Michael Lewis is Software Engineering Manager for Gyro Stabilized Systems, LLC. Michael has designed and developed control systems and embedded software solutions for over 15 years and holds a BSEE from LeTourneau University.
We take a close-up look at inertial measurement and inertial navigation in autonomous cargo transport. High standards for technology in the lab and in the factory are all very fine, but what matters most is how it works in industrial application. This free webinar also examines oil and gas pipeline inspection and stabilization of optical camera platforms
Learn about them all in this free webinar on November 17.
Three experts in the application of inertial technology discuss the challenges they confront daily in their respective fields, and how they achieve rock-solid success with gyroscopes from KVH.
In the fast-deveoping field of drone delivery, an exciting start-up is bringing same-day shipping to everyone in the world: the first autonomous drone capable of delivering 300 to 500 pounds of cargo over a 300-mile range, with no need for an airport or electric charging station. Elroy Air recently announced a partnership with NASA to accelerate the integration of autonomous cargo aircraft in the U.S. Its current Chaparral model boasts a hybrid-electric powertrain and the ability for autonomous cargo loading and unloading, allowing a single pilot to operate a fleet of 10–50 UAVs from a remote location. Again, the inertial sensor proves essential to mission accomplished.
In the inspection of oil and gas pipelines, gyroscopes within a “pig” that travels the internal length of the pipeline, from 900 meters to 900 kilometers, give the centerline coordinates as well as measurement of any bending strain on the conduit. Onstream Pipeline Inspection Services looks for integrity threats such as corrosion, deformation and strain events. Inertial mapping units are used for calculation of bend strain and to give positional information to be able to locate the other threats correctly. Their main challenges are size, low power consumption, inertial accuracy, gyro rate and ITAR restrictions.
For sight optimization of optical payloads on air, land and sea, Gyro Stabilized Systems designed an open architecture platform that is versatile and interchangeable, adapting to different gimbals that may carry infrared, corona cameras, radiometric sensors, gas detection, still cameras, broadcast cameras, and cinema production with long lenses. Their byword is diversity, with the ability ability to customize and quickly switch out sensor payloads. The presentation includes a quick gimbal tutorial, what to look at when selecting sensors, the caveats and tradeoffs in building 5-axis and 6-axis systems with innovative steer and control modes. Results of payload stabilization in helicopters and other moving platforms demonstrate that at the heart of success is a really good inertial sensor.
Buddy designs the navigation apparatus for this autonomous aerial cargo aircraft systems developer. He has a Ph.D. in autonomy and artificial intelligence from the Massachusetts Institute ofTechnology and is a licensed private pilot.
Stephen Westwood Senior Director, Engineering and Technology Onstream Pipeline Inspection Services
Stephen brings over twenty years of design experience in In Line Inspection tools. He holds a PhD inExperimental Magnetism and BSc in Experimental Physics. Stephen’s expansive knowledge of pipeline inspection tool development includes algorithm development and magnetic design of In LineInspection tools. Previous roles have seen Stephen building and leading multi-disciplinary groups in new product development throughout his career. Stephen’s industry knowledge, experience and unparalleled reputation will be a driving factor in Onstream’s continued development and growth within the In Line Inspection industry.
Michael Lewis Software Engineering Manager Gyro-Stabilized Systems
Michael Lewis is Software Engineering Manager for Gyro Stabilized Systems, LLC. Michael has designed and developed control systems and embedded software solutions for over 15 years and holds a BSEE from LeTourneau University.
Buddy Michini
Stephen Westwood
Michael Lewis
Buddy Michini
Stephen Westwood
Michael Lewis