European Union (EU) transport ministers have agreed to take action to make autonomous driving a reality across the 28-nation bloc.
The Amsterdam Declaration was signed by the ministers during an informal meeting of the Transport Council on April 14 in Amsterdam.
The declaration outlines the steps necessary for the development of self-driving technology in the EU. In the document, the Netherlands, the European Commission, EU member states and the transport industry pledged to draw up rules and regulations that will allow autonomous vehicles to be used on the roads.
Specifically, they agreed to:
promote a consistent legal framework for driverless driving throughout Europe
develop a policy to deal with connected and automated-vehicle data
work toward an internationally compatible vehicle-to-vehicle and vehicle-to-infrastructure system
cooperate to ensure cyber security
increase acceptance of connected and automated vehicle technologies
“Our industry welcomes the Declaration of Amsterdam as an important milestone that promotes much-needed cooperation between automobile manufacturers, national governments and the EU institutions,” said Erik Jonnaert, secretary general of the European Automobile Manufacturers’ Association (ACEA).
Connected, cooperative and automated driving developments should come together to harvest societal benefits. (Chart from Amsterdam Declaration)
A new PolaRx5 Continuously Operating Reference Station (CORS) platform, offered by Septentrio Americas, is optimized for state departments of transportation (DOTs) and other real-time-kinematic (RTK) network operators.
The Septentrio PolaRx5 GNSS receiver.
The PolaRx5 CORS receivers can be purchased at special pricing by UNAVCO member organizations and affiliates. Septentrio has been selected by UNAVCO as the preferred vendor of CORS receivers under a multi-year agreement.
The PolaRx5 is powered by Septentrio’s AsteRx4 next-generation multi-frequency engine. It offers 544 hardware channels and supports all major satellite signals including GPS, GLONASS, Galileo and BeiDou, as well as regional satellite systems such as QZSS and IRNSS.
Septentrio’s Advanced Interference Mitigation (AIM+) technology enables the PolaRx5 to filter out both intentional and unintentional sources of radio interference, from narrowband signals over high-powered pulsed signals to chirp jammers and Iridium transmitters.
In addition, Septentrio’s patented APME+ multipath mitigation technology guarantees superior measurement quality by eliminating short-delay multipath errors without introduction of bias, the company said.
The PolaRx5 leverages Septentrio’s web interface and built-in Wi-Fi and Bluetooth interfaces to give users complete control and visibility of the receiver. The user interface integrates into existing network management systems. The web browser provides secure access to all receiver settings and status, data storage and firmware upgrades, as well as a built-in spectrum analyzer for system monitoring.
“The multi-constellation PolaRx5, with its powerful interference and multipath mitigation and new Web interface, is the ideal solution for DOTs to modernize their aging CORS installations to the newest GNSS technology,” said Neil Vancans, vice president of Septentrio Americas.
KVH Industries is developing a fiber optic gyro (FOG)-based, low-cost inertial sensor for self-driving cars.
The company also released a Developer’s Kit to assist design engineers with integrating FOG technology into driverless car control systems.
KVH’s high-precision FOG is key to a driverless car’s performance. In this photo, the red illumination represents light moving through the FOG’s optical circuit of coiled fiber; this circuit is the FOG’s sensing unit — it is mounted with power and processing electronics within a driverless car to provide precise data for the car’s navigation systems.
FOGs and FOG-based inertial measurement units (IMUs) are key parts of the sensor mechanisms that are essential for highly accurate autonomous car performance, KVH said. For example, FOGs provide precise azimuth measurements that an autonomous car’s logic processing unit and control systems need to determine motion through a curve.
An IMU — which includes FOGs and accelerometers in one compact package — also provides highly accurate 6-degrees-of-freedom angular rate and acceleration data to precisely track the position and orientation of the car even when GPS is unavailable, helping the car stay on course.
As a manufacturer of high-performance sensors and integrated inertial systems for defense and commercial guidance and stabilization applications, KVH Industries has experience in autonomous vehicle prototype programs and unmanned applications.
“Extremely precise heading based on fiber-optic gyro technology is absolutely essential for autonomous vehicle performance,” said Martin Kits van Heyningen, KVH’s chief executive officer. “This is something we learned from having been involved with more than a dozen driverless car development programs over the years.”
“What we are seeing now is that each driverless vehicle concept in development around the world is being designed in a unique way,” said Kits van Heyningen. “With so many different possibilities, developers can accelerate their progress by working with a proven technology such as KVH’s FOGs and FOG-based IMUs and leveraging our experience to ensure their success.”
Developer’s Kit. The new Developer’s Kit includes the user interface software and all components needed to connect a KVH FOG or FOG-based IMU to a computer to configure, analyze and test a unit. “The kit is designed to help engineers get up and running in minutes, making it easier to run diagnostics and accelerate their system development,” said Roger Ward, KVH’s director of FOG product development.
Driverless cars represent one of the fastest areas of autonomous-systems development. Transportation experts, automotive manufacturers and engineers alike predict that driverless cars will be commonplace soon.
An updated policy concerning automated vehicles will soon be published by the National Highway Traffic Safety Administration (NHTSA), which is part of the U.S. Department of Transportation. “The rapid development of emerging automation technologies means that partially and fully automated vehicles are nearing the point at which widespread deployment is feasible,” NHTSA said.
“We have successfully produced more than 90,000 fiber-optic gyros for an extensive range of unmanned applications, in part because of our ability to tailor size, performance, and cost to meet different design needs,” said Jeff Brunner, KVH’s vice president for FOG operations. “Controlling the entire FOG design and manufacturing process gives us that advantage, and makes it possible to produce a low-cost sensor when driverless cars enter full-scale production.”
KVH’s FOGs and FOG-based IMUs are in use in prototype programs not only for autonomous cars, but also for production programs for underwater unmanned vehicle navigation and rail/track geometry measurement systems, to name just a few.
The KVH 1750 IMU.
In addition, KVH’s inertial products have been widely adopted for commercial applications such as land-based street mapping platforms, unmanned aerial systems, camera stabilization systems and remotely operated subsea systems.
As more and more programs and platforms use KVH’s inertial products, they are becoming the reference standards of the unmanned world. For example, KVH’s 1750 IMU was an integral part of 11 of the 23 humanoid robot finalists in last year’s DARPA Robotics finals, a competition designed to showcase robots capable of intervening for and even replacing humans in high-risk situations such as fires, earthquakes, and other natural disasters.
“Our IMUs and inertial sensors have already been used in a wide range of products and applications, and we know that it’s just the beginning,” said Kits van Heyningen. “We are thrilled to play a role in these exciting developments and emerging applications that are literally changing everyday life.”
INRIX Inc., a connected car services and movement analytics company, has released a redesigned version of INRIX Traffic for iOS and Android.
INRIX Traffic is a next-generation navigation and traffic app that learns user preferences to take the guesswork out of driving. The app integrates with a user’s calendar and learns their driving habits to create a personalized itinerary that includes automatic alerts, anticipated trips, favorite destinations and preferred routes.
Available worldwide now in the Apple App Store and Google Play, INRIX Traffic learns routines and preferences as users go about their day. INRIX Traffic adds favorite places automatically instead of requiring users to spend time inputting destinations such as home, work or school.
Based on learned activities, it creates a daily, driver-specific itinerary of anticipated trips, as well as frequent and preferred routes. By accessing calendar information on a mobile device, the app also adds events with addresses to the daily driving itinerary.
Unlike other driving apps that can provide inaccurate traffic and incidents based purely on consumer input, INRIX Traffic uses a massive crowd-sourced network of more than 275 million connected cars and devices to offer accurate map and real-time information.
INRIX Traffic proactively monitors road conditions to alert drivers of ideal departure times, changes to arrival times and optimal routes to frequent or scheduled destinations based on real-time traffic.
“We designed INRIX Traffic with one specific vision: To help drivers move through their daily lives as quickly and efficiently as possible. The app uses our advanced traffic science to make even routine trips easier,” said Bryan Mistele, president and CEO, INRIX. “Users want an app that is accurate, personalized and smart enough to work proactively for them — so we’ve integrated several highly advanced technologies into one all-encompassing app.”
INRIX Traffic uses the crowd-sourced and free OpenStreetMap (OSM) for map data. By leveraging the power of user-generated content around the world, OSM can quickly adapt to the ever-changing road network. Using OSM enables INRIX to bring a high-quality map and turn-by-turn navigation to users at no cost and without advertisements. In addition to reporting incidents along their route including accidents, police activity and road hazards, INRIX Traffic users can send map feedback directly from the app.
INRIX Traffic is powered by the same technologies the company delivers to its automotive customers such as Audi, BMW, Lexus, Mercedes-Benz and Porsche. These connected car services include real-time and predictive traffic, off-street parking information and drive-time alerts. INRIX will continue integrating features from its product portfolio into future versions of INRIX Traffic.
INRIX Traffic is available in eight languages in 16 countries across North America and Europe, including Canada, France, Germany, Spain, United Kingdom and United States, with additional countries coming soon.
The app is built on Autotelligent, the company’s new software development kit and integrated cloud platform that provides machine learning and route monitoring. Autotelligent can be integrated into products in multiple industries such as automotive, enterprise and mobile.
Omata is introducing a new analog GPS speedometer that displays the information most essential to the activity in a classic form.
Starting with cycling, Omata introduces the Omata One speedometer, designed to complement and maintain the purity of the ride as well as look beautiful on the bike.
On the inside of the speedometer is a GPS computer that records with high precision so that cyclists can at download their activity data to their preferred training applications or sites.
On the outside Omata One has a legible and mechanical analog movement that shows riders the speed, distance, ascent and time. The company’s first product displays only these four, core pieces of information so the cyclist can focus on the ride.
“Everything about your bike should be as pure, inspiring and beautiful as the ride itself,” said the Omata team in a press release. “We are a team of ruthlessly dedicated and committed product makers who believe great design and meaningful products come more from what you leave out, rather than what you add in.”
The Omata One speedometer will launch on Kickstarter on April 5 with estimated delivery of the first product in February 2017. Omata One will subsequently be available through omata.com.
Aerial refueling requires highly precise relative navigation. (ILLUSTRATION: Charles Park)
Future UAVs will require relative navigation capability to fulfill a broad range of assisted manned and unmanned missions. A new approach, demonstrated in application to aerial refueling, provides access to accurate relative time-space positioning information (R-TSPI) between platforms.
By Shahram Moafipoor, Jeffrey A. Fayman, Lydia Bock and David Honcik
The advent of unmanned aerial vehicles (UAVs) highlights the importance of precise relative navigation information for safe use of UAVs in many application areas. Future military and civilian UAV applications will increasingly require capabilities such as
sense and avoid
swarming
vehicle-to-vehicle (V2V) platooning
docking
autonomous landing and
autonomous aerial-refueling,
all of which require access to accurate relative time-space positioning information (R-TSPI) between platforms.
In this article, we present the foundation for a generic approach to relative navigation capable of meeting the full range of relative assisted manned and unmanned operations. We present a relative extended Kalman filter (R-EKF) that integrates line-of-sight relative observations from GPS as well as non GPS-based onboard sensors measuring relative bearing and/or relative distance. Multi-sensor fusion provides enhanced system integrity and robustness to partial or total lack of GPS-satellite navigation (GPS-denied). The relative navigation system described here uses these technologies, providing up to 100 Hz R-TSPI with an accuracy of up to ±1.0 m (a function of relative distance), ±0.1 m/s velocity and ±0.5º attitude. The system can be applied to a variety of relative navigation applications; here we focus on its use in aerial refueling.
132d Air Refueling Squadron. A Boeing KC-135R Stratotanker refuels an F-22A Raptor. (Photo: USAF)
AERIAL REFUEL CHALLENGES
Automated aerial refueling for manned and unmanned platforms is a challenging problem requiring accurate R-TSPI. The Geo-RelNAV system provides a key measurement for aerial refueling: the vector closure rate, the differential velocity between the tanker and refueling aircraft. The closure rate is monitored in real time onboard the tanker. The measurement can be used to:
maintain safety-of-flight by ensuring refueling aircraft do not exceed a certain velocity,
determine whether or not a refueling aircraft is approaching the tanker with sufficient velocity, and
provide data to drogue-control engineers to improve control law design.
As a GPS/INS system, Geo-RelNAV can produce a relative navigation solution at a faster sample rate than GPS alone. Solutions are available via serial and/or Ethernet (both TCP and UDP) providing input to external systems as well as the tools for analysis engineers to monitor the data in real time using standard monitoring and recording tools. The system provides R-TSPI in different frames, including the body frame of the platforms, local navigation frame (wander-azimuth) and Earth-fixed frame, as well as transferring the solution to arbitrary points of interest on the aircraft such as the refueling aircraft’s refueling probe.
RELATIVE INERTIAL NAVIGATION
We use the terms primary and secondary in this article to identify the platforms for which R-TSPI data is being generated. R-TSPI is always provided for the primary with respect to the secondary. Referring to Figure 1, the tanker is considered the primary and the refueling aircraft, the secondary (or vice versa, depending on the location of the control segment). Data is always transmitted through the data link from the secondary to the primary. Figure 1 summarizes the geometric relations, where the primary body frame is labeled p-frame and the secondary body frame is labeled s-frame. The body frame fixed to the primary (P) is shown by (xPp,yPp,zPp), and body frame fixed to the secondary (S) is shown by (xSs,ySs,zSs).
Fgure 1. Primary/secondary geometry and corresponding body frames fixed to the vehicle body.
The relative navigation equation is set up for the state of the secondary with respect to the state of the primary in the center of the body frame of the primary, p-frame:
(1)
where xPp is the primary position vector established in the p-frame, and xSp is the secondary position vector defined in the p-frame. Note that these vectors can also be obtained from the primary/secondary strapdown inertial navigation solutions after transferring to the reference (eccentric) point. Equation (1) represents the fundamental equation, from which the relative navigation equations are derived. Once the relative kinematic model of the position and velocity are established, the next step is to develop the relative attitude kinematic model. The relative attitude, denoted by the quaternion qpS, is used to map vectors in the s-frame to vectors in the p-frame:
(2)
where qp and qs are the quaternion attitudes of the primary and secondary with respect to the i-frame, qp* is the conjugate of qp, and is the quaternion multiplication operator.
Hardware for the relative navigation system.
RELATIVE EXTENDED KALMAN FILTER
To establish the R-EKF, we must derive the relative inertial error equations. The R-EKF has 21 basic states including nine for relative position, δΔxpPS , relative velocity, δΔvpPS , and relative attitude, Ψpps, and 12 to model the primary’s gyro and accelerometer bias (non-constant) and non-linear scale factors. Since the relative distance between the secondary and primary is small compared to the radius of the Earth, the gravity terms are negligible. Thus, in the linearized terms, the relative gravitational terms are ignored. It should be noted that the secondary states are assumed to be known for retrieving the absolute primary TSPI information. Since Equations (1) and (2) can only provide the general dynamic model for a nonlinear state model, all these equations must be linearized using Taylor series about nominal values (neglecting the higher-order terms). After perturbation state equations are established, they should be discretized from a continuous-time to a discrete-time sequence. The final solution to the state equation can be expressed as:
(3)
with:
(4)
FPpS is the Jacobian matrix, and the perturbation elements are all related to the primary:
(5)
RELATIVE GPS MEASUREMENT MODEL
When GPS is available, high-accuracy relative positions are derived from the use of carrier-phase differential GPS, a technique commonly used in static positioning applications such as surveying. However, unlike those applications, in this case the reference receiver is not stationary; it is located on a moving platform (secondary) creating a moving baseline. The relative GPS measurement in our system is provided by epoch-by-epoch (EBE) differential carrier-phase processing, which measures accurate relative position between the secondary and primary systems. The EBE relative position has a typical accuracy better than 3 cm (1-sigma horizontal) and 6 cm (1-sigma vertical). Testing of the relative measurement was conducted using two ground vehicles configured with 10-Hz dual-frequency GPS sensors. The mean difference was less than 5 cm. As a conclusion, the GPS relative mode was shown to provide accurate relative positions between the platforms. Once the relative position is measured, the R-EKF observation model can be established as:
(6)
The (ΔxpPS )GPS term is the relative position measured by using GPS data, and the term (ΔxpPS)INS is the relative position, which is predicted by using the last updated inertial solutions. Note that in order to use this relative observation, the lever-arm vector between the GPS and IMU of both the primary and the secondary must be accurately measured and applied (see Figure 2).
Figure 2. Relative observation model.
Here, the observation model is represented on the condition that the vector of observations has yielded certain values based on an assumed linear relationship to:
(7)
Equations (3) and (7) are the fundamental equations of the R-EKF.
SYSTEM ARCHITECTURE
Relative navigation is computed and provided at one of the units, designated the primary unit. This requires data from the secondary unit to be transferred to the primary unit over a data link. The primary unit uses this transmitted data to calculate its position, velocity and attitude relative to the secondary unit. Figure 3 summarizes the architecture and data-flow. Mathematically, the data from the secondary unit used in the relative calculations are assumed to be errorless.
Figure 3. Geo-RelNAV architecture.
OPERATIONAL ENVIRONMENT
We distinguish the following three relative navigation stages, illustrated in Figure 4, where each phase utilizes a unique processing mode.
Fgure 4. Relative navigation phases.
In the Approach phase, the data link between primary and secondary units is not closed. An autonomous navigation solution for both the primary and secondary units is computed on each platform independently. This information will be later used when the system transitions to the Engagement phase to initialize the R-EKF.
In the Engagement phase, the data link between primary and secondary units is closed, and the R-TSPI solution is computed between the platforms. Sensor observations are transmitted across the data link from the secondary unit to the primary unit. The primary unit implements the R‑EKF to produce the R-TSPI solution.
In the Departure phase, the activity requiring R-TSPI (that is, refueling) is complete, and the secondary platform pulls away from the primary platform. In this phase, we transition from the R-EKF back to the autonomous independent navigation system.
The Approach phase is as important as the Engagement phase in attenuating the initialization error in terms of position, velocity and attitude. To initialize the R-EKF, the autonomous TSPI solution from the secondary unit is transferred to the primary unit, where the initial relative position, velocity and attitude are estimated.
There are three conditions under which this initialization must occur:
upon transition from the Approach phase to the Engagement phase,
when in the Engagement phase and the system experiences a data link dropout, and
when there is a large latency in the data link. If the data link latency is too large, the data arriving at the primary can no longer be used.
VALIDATION TESTING
Several system tests were conducted including static bench testing, dynamic ground vehicle testing and flight testing. We discuss the results for the static and bench testing here.
For static bench testing, the system was set up on two points with a measured fixed displacement. The sensor configuration included dual-frequency GPS receivers, ring laser gyro-based IMUs, and a data link operating in the 900-MHz frequency band.
The results show that relative position held to the fixed offset with a standard deviation of less than 0.1 m in North, East and Up. Relative velocity held to zero with a standard deviation less than 0.01 m/s, and relative attitude was also maintained with the accuracy up to the gyro bias stability of the ring laser gyro IMU (1°/hr for a stationary platform).
The overall performance of the system in static bench test confirms the stability of the hardware and software of the system, when it is not exposed to any dynamics, and the sensors are in close proximity (no data link latency or data dropouts).
Dynamic Drive Test. In a more realistic test to simulate the operational phases described in Figure 4, the drive test followed a scripted path. As shown in Figure 5, the two platforms left Geodetics’ facility and drove separately (simulated Approach) until they met each other at the Fiesta Island test site, where the data link was closed for the Engagement phase. The primary and secondary navigation systems operated independently during the Approach phase.
Figure 5. Drive test ground trajectory of the primary (blue) and secondary (red).
Once the data link was closed at the test site, the R-EKF engaged, using initialization information transmitted from the secondary to the primary platform. To provide a “truth source” for evaluating the performance of the relative navigation solution, both autonomous GPS/IMU systems were fed data from an external reference receiver. Table 1 shows the statistical data analysis in the form of mean and standard deviation for the collected data.
Average RMS of fit in the relative position, velocity and attitude of approximately 1.0 m, 0.1 m/s and 0.3º, respectively, were computed for the entire relative navigation period. In this dynamic test, we encountered frequent data link dropouts, data link latency, as well as GPS outages, causing discontinuity in the R-EKF measurement updates until GPS was reacquired. During these periods, the R-EKF prediction model, updated with the last calibrated IMU data, provided the R-TSPI. This test help confirm that system performance is at the expected levels, even in the presence of real-world data link and GPS problems.
Table 1. Statistical analysis of the R-TSPI solution.
GPS-DENIED OPERATIONS
Over-reliance on GPS has exposed vulnerabilities associated with this technology. For example, GPS is easily jammed and spoofed. While spoofing can be addressed with Selective Availability Anti-Spoofing (SAASM) technology, and advances such as M-code will mitigate other vulnerabilities, systems of the future must be robust to partial or total lack of GPS. Advanced sensor-fusion technologies are necessary to provide capabilities in conjunction with, and in the absence of, GPS.
In the context of aerial refueling, sensors such as active and passive vision systems can be used as complimentary observations by the system, providing a GPS-free relative distance observation in situations where GPS is blocked due to airframe masking, jamming, and so on.
Data from both active (lidar) and passive (camera) vision sensors were added to the system, providing significant advantages in the process flow. The use of vision sensors provides the relative distance observation in GPS-denied conditions for continuity in R-EKF updating. In addition, vision-based relative distance allows for the detection of outliers by evaluating the redundancy contribution of the measured GPS-based relative distance, and enables the transfer of the R-TSPI solution from the secondary refueling center to the on-the-fly probe-drogue system, as shown in Figure 6.
Figure 6. Vision sensor aiding increasing the integrity
For the active vision system, we leveraged a fully integrated lidar mapping payload as shown in Figure 7 (left). For the passive sensor, we utilize a stereo camera. Figure 7 (right) shows the test area and the simulated drogue. Imagery observations from the passive camera and the lidar system were processed with independent algorithms appropriate to each data type and the relative distance between each of the two sensors, and the simulated drogue was measured with an RMS error of less than 10 cm.
Figure 7. Geo-MMS (left) and its application (right) for measuring relative distance.
INTEGRITY
While outside the scope of this article, in addition to supplying a GPS-free relative distance observation, the use of vision sensors was applied to the task of increasing system integrity. This includes, in general, the capability to indicate when the system should not be used for the intended operation. We focused on two aspects: outlier detection (inner reliability), and the effect of undetected outliers (outer reliability).
To properly address the reliability and integrity requirements, a quality testing mechanism was designed to assess the estimated/predicted relative distance observations before passing them in to the R-EKF module.
CONCLUSIONS
An autonomous relative navigation, in its application for the aerial refueling problem, places special attention on system architecture so that it can handle most possible real-world scenarios, including frequent data link dropouts, data link latency and GPS outages. The core of the system is a relative extended Kalman filter, which uses GPS and IMU measurements of the primary and secondary platforms to estimate the relative inertial navigation states. The system is able to provide relative TSPI at the IMU sample rate with an accuracy of ±1.0 m position, 0.1 m/s velocity and ±0.5º attitude.
An added benefit of the system architecture is the ability to add observation models that do not rely on GPS. Thus, redundancy can be introduced using sensors such as vision systems.
SHAHRAM MOAFIPOOR is a senior navigation scientist at Geodetics, focusing on new sensor technologies, sensor-fusion architectures, application software, embedded firmware and sensor interoperability in GPS and GPS-denied environments. He holds a Ph.D. in geodetic science from The Ohio State University.
JEFFREY A. FAYMAN serves as Geodetics’ CTO. He holds a Ph.D. in computer science from the Technion Israel Institute of Technology and has published more than 40 papers in robotics, computer vision, computer graphics and navigation systems.
LYDIA BOCK serves as Geodetics’ president and CEO. She has more than 35 years of industry experience spanning a variety of high-tech industries including electronics, semiconductors and telecommunications. She has a Ph.D. from the Massachusetts Institute of Technology.
DAVID HONCIK, Geodetics’ director of engineering, has more than 30 years of experience in software/hardware integration and structured software design for real-time embedded systems, Windows programs, graphics, telecommunications, aerospace, flight simulation and airborne instrumentation.
The integrated lidar mapping payload referenced is Geodetics’ Geo-MMS system.
iXBlue — a subsea navigation, positioning and imaging systems company — is offering two new positioning sensors.
Fifth-generation Octans
iXBlue is offering its customers the opportunity to upgrade their fourth-generation Octans positioning reference system to the fifth-generation system. The fourth-generation Octans was manufactured beginning in January 2014.
Built on iXBlue’s high-performance fiber-optic gyroscope technology, the Octans is an all-in-one gyro compass and motion sensor (attitude and heading reference system) with features such as IMO/IMO-HSC certification. The upgraded system provides extremely accurate real-time output for roll, pitch, heading and heave, as well as acceleration and rate of turns under challenging GNSS-denied environment.
Heading measurement accuracy has been doubled over the fourth-generation Octans: with still 0.1° Seclat in stand-alone, the system can now provide 0.05° Seclat with GNSS.
Moreover, the fifth-generation Octans now offers the ability to align on transit and the extended capability to deliver, in real time, accurate heave for swells up to 30 seconds.
The offer from iXBlue includes both the upgrade and calibration, backed by a five-year warranty.
Rovins Nano for remotely operated underwater vehicles (ROVs)
iXBlue has also launched a new inertial navigation system for the offshore industry, the Rovins Nano.
Based on iXBlue’s fiber-optic gyroscope technology, the Rovins Nano has been designed for ROV pilots performing maintenance and construction operations. It offers the stability and accuracy of the inertial position, outputting true north, roll, pitch and rotation rates.
“Rovins Nano is able to directly transmit the ROV’s position with extreme accuracy thanks to its integrated INS algorithm capable of collecting acoustic data,” said Paul Wysocki, iXBlue Rovins Nano product manager. “This is now possible regardless of the depth at which it is located: it is therefore not just an evolution, but rather a revolution for the middle water station keeping.”
Where the Doppler Velocity Log (DVL) has limitations, especially when operating in middle water, Rovins Nano is now there to guarantee optimal navigation safety.
“In the future, it will no longer be necessary to use a DVL,” Wysocki said. “Even in ‘sparse array’ LBL fields, with the presence of only one or two beacons, the combination between Rovins Nano and our Ramses acoustic system enables us to reach extremely accurate positioning data.”
A science ROV being retrieved by an oceanographic research vessel.
iXBlue provides more flexibility to its customers: by avoiding the use of DVL, operators reduce their operational and associated calibration costs.
Besides its high level of performance, Rovins Nano adapts itself to the user: the configuration, installation and product’s use have been considerably facilitated, while incorporating a system as complex as the inertial navigation system (INS). The ultimate goal is for the pilot to forget the existence of the product when maneuvering. Moreover, thanks to its compactness, lightness and open architecture with all third-party sensors, Rovins Nano is easy to integrate.
The French high technology company iXBlue is now offering an expanded range of subsea navigation systems, from ROV navigation to survey applications.
Veripos, a global supplier of high-precision GNSS positioning services to the offshore oil and gas industries, has extended its ranges of proprietary software with the introduction of Quantum, a new, all-purpose suite of visualization modules providing a state-of-the-art user interface to support next-generation services and features.
Designed to operate with all current Veripos positioning options including its latest Apex5 multi-constellation PPP service (see below), the new software has been developed with significant input from a wide range of users by way of simplifying any system configuration while easing methods of interpretation. Other advances include integral diagnostic functions for simple identification of operational problems together with indications of likely solutions.
Visualization modules can also be operated independently without affecting concurrent positioning calculations which might otherwise be feeding critical survey or vessel systems.
At the same time, the Quantum framework comprises a series of different modules to meet a variety of specific operational tasks such as those necessary for hydrographic and seismic surveying as well as dynamic positioning. Its versatility also extends to providing a basic foundation for accommodating new modules or features.
Apex5 PPP service launched
Veripos has extended its Apex service with introduction of Apex5, which is capable of receiving observations from five available satellite constellations comprising GPS, GLONASS, Beidou, Galileo and QZSS.
Using precise point positioning (PPP) methods for correction or modeling of all GNSS error sources, the new multi-constellation service with its access to increased civilian signals ensures greater power levels via interoperable networks in addition to improved levels of observation and redundancy. Other advantages include a higher satellite count and position availability, particularly in masked and scintillated environments.
Calculations are based on Veripos’s own orbit and clock determination system (OCDS) which derives real-time corrections for all available satellite constellations using proprietary algorithms. The OCDS uses data from the company’s own global network of reference stations with multiple and redundant systems supported by dedicated network control centres in Aberdeen and Singapore.
Apex5 is broadcast alongside existing Apex, Apex2 and Ultra services via seven geostationary satellites to ensure continuous availability and service redundancy. Typical position accuracies are better than 5cm horizontal at the two sigma (95 percent) confidence level.
PLK Technology has selected Telit’s SL869-V2 GNSS IoT (Internet of Things) module to deliver positioning functionality for Optian, a new product combining the features of an Advanced Driver Assistant System (ADAS) and a high-end automotive black box.
Telit’s SL869-V2 is a subminiature multi-satellite receiver module that can be installed in vehicles, industrial, wearable and portable digital devices. It delivers a high level of stability for navigation applications by tracking GPS and GLONASS at the same time, relaying accurate and fast-refreshing positioning information.
PLK’s Optian takes the functionality of a typical black box capable of post-processing accidents, and adds ADAS capabilities to implement accident prevention measures, delivering lane departure warning, forward collision warning and front car departure alert functions. Optian uses the Telit SL869-V2 GPS module to sense displacement, from which it derives speed and distance between cars to warn the driver about the risk of collision.
ADAS are systems found in modern vehicles designed to automate, adapt and enhance vehicle safety and driver experience. Safety features in ADAS include warnings for collision and accident avoidance which help drivers implement safeguards, and sharpen their focus on control of the vehicle.
Adaptive ADAS features help by automating lighting, providing adaptive cruise control and autonomous braking, incorporating GPS and traffic warnings, connecting smartphones, alerting drivers about dangerous driving situations, keeping the driver within the lane of traffic and enhancing visibility of the vehicle’s blind spots.
PLK started in 2000 as an in-house venture firm as part of Hyundai Motor Company and was later spun off in 2003. It specializes in the development and production of ADAS, utilizing camera image sensors to recognize lanes, vehicles, light sources, traffic lights and pedestrians.
PLK was the first to develop a Lane Departure Warning System (LDWS) based on color image recognition and, in 2006, became the first to line-fit it into vehicles (Hyundai Motor Company).
PLK systems quickly became widely recognized for their performance and, have since 2009 been equipping 15 models around the world, including in the United States, Europe, the Middle East, China and Australia, in addition to Hyundai and KIA passenger cars.
“It is rewarding to secure the Optian project for Telit’s GNSS module. The selection process was very stringent and PLK’s choice of the SL869-V2 is a testament to the quality and performance of the product,” said Steven Kim, senior sales director of Telit Korea. “Telit GNSS modules are not only successful in the automotive sector but also in various other industries. We expect that cooperation with PLK will expand as they continue developing innovative systems and products that make driving a safer experience for motorists everywhere.”
Advanced Scientific Concepts (ASC), supplier of 3D flash lidar vision systems for terrestrial, aerial and space applications, is creating of Advanced Scientific Concepts LLC, following the sale of its ASCar division to Continental AG.
With the acquisition of ASCar, Continental plans to mass produce flash lidars at an affordable price to support the commercial automotive industry.
Advanced Scientific Concepts LLC will continue to focus on providing 3D flash lidar custom and standard product solutions for space, manned airborne and underwater applications. This includes also providing UAS, autonomous vehicle and 3D mapping solutions for the domestic and international military markets.
“ASC’s product line for military and aerospace has matured over the past couple years to a high technology readiness level (TRL) through rigorous design and development,” said Jim Curriden, president of ASC LLC. “ASC LLC will now be entirely focused and well positioned to provide affordable solutions for the military and aerospace community by providing either off the shelf or tailored products to meet a user’s unique requirements.”
Advanced Scientific Concepts LLC is aimed at concentrating on the key markets at the foundation of their technology, ready to invest in the future advancement of 3D flash lidar.
President Obama’s trip to Cuba this week marks a historic milestone in the normalization process between the U.S. and Cuba. At the same time, the two countries are working to improve maritime navigation safety and related areas of mutual interest to protect lives and property at sea.
Ambassador Jeffrey DeLaurentis, the chief of mission at the U.S. Embassy in Havana, and Col. Candido Alfredo Regalado Gomez, chief of Cuba’s National Office of Hydrography and Geodesy (ONHG), signed a Memorandum of Understanding (MOU) on maritime navigation.
The MOU calls for cooperation in the areas of hydrography, oceanography, geodesy and related services of mutual interest. One of the major focuses will be to improve maritime navigation safety including efforts to ensure the accuracy of both electronic and paper charts, eliminate charting overlaps and fill in gaps in navigational chart coverage.
In addition to updating data on domestic charts like the NOAA chart above, the U.S. and Cuba agreed to work together on a new international paper chart which will cover south Florida, the Bahamas and northern Cuba. (NOAA)
In February 2015, less than two months after President Obama announced the United States’ new approach toward Cuba, the National Oceanic and Atmospheric Administration (NOAA) and the ONHG, through a set of reciprocal exchanges, launched what became a year-long effort to formulate the technical exchange that is a normal course of affairs between most of the other maritime nations of the world. Both agencies are working on plans for monitoring and forecasting tides and currents for ports and improving positioning networks among other related scientific and technical activities.
“NOAA has a strong interest in both improving navigational safety and in protecting the marine environment in the heavily travelled and vibrant waters between our two countries in the Straits of Florida,” said Russell Callender, Ph.D., assistant NOAA administrator for the National Ocean Service. “We welcome this agreement and the progress it represents.”
“Improved navigation services are important for commercial mariners and individual boaters alike,” said Ambassador DeLaurentis, “and it is particularly important as authorized trade and authorized travel increase between the two countries.”
“This MOU will allow us to fill gaps in essential navigational data, working on a practical level with our Cuban counterparts,” said Kathryn Ries, deputy director of NOAA’s Office of Coast Survey. “The U.S. works with hydrographic offices of all nations that have waters adjacent to the United States and our territories, and this agreement improves the exchange of charting information with Cuba as well.”
The MOU is the first step in what is expected to be a long-term collaboration between the two countries.
In addition to aligning each country’s navigational charts, NOAA and ONHG are sharing data for the creation of a new international chart (known in mariner’s parlance as “INT chart”) 4149, which will cover south Florida, the Bahamas, and north Cuba. NOAA plans to publish the new chart this year.
Sierra Wireless has released an advanced fleet management feature to support the company’s AirLink GX450 mobile gateway, allowing it to collect OBD-II vehicle telemetry data.
The added functionality will enable large organizations and fleet management solution providers to rapidly develop applications to monitor vehicle health and performance, helping them reduce costs, streamline operations and increase efficiency.
Managing a vehicle-based workforce involves a large group of stakeholders, including operations, IT and fleet management. By combining mobile networking and rich vehicle telematics onto a single platform that gathers and reports vehicle diagnostic data directly to applications, this new feature will simplify and centralize vehicle management across an organization. Organizations will no longer need to purchase a separate in-vehicle telematics platform to gather and monitor vehicle health data.
“We added advanced, easy-to-use telemetry to the AirLink GX450 to enable customers to simplify the adoption of vehicle telemetry solutions, including the ability to leverage their existing investment in fleet communications equipment,” said Jason Krause, senior vice president, Enterprise Solutions, Sierra Wireless.
Clevest, a provider of mobile workforce management solutions for utilities, has worked closely with Sierra Wireless through the development of the AirLink GX450’s vehicle telemetry feature to produce a complete workforce management and vehicle monitoring solution.
“Our mobile workforce platform is tightly integrated with AirLink gateways,” said Edna Menon, senior product marketing manager, Clevest. “With the GX450 telemetry feature, our utility customers can take advantage of robust vehicle diagnostic capabilities, in addition to the reliability and ease-of-use of our integrated solutions.”
The AirLink GX450 vehicle telemetry uses an optional OBD-II accessory to collect vehicle diagnostic data and send it to a remote server using an open messaging protocol (MQTT). Vehicle telemetry is designed for applications in public safety, utilities, emergency and field services, and for large organizations or fleet management solution providers that have the in-house resources to develop their own vehicle monitoring applications.
