Tag: autonomous robots

Taoglas introduces ultra-compact dual-band high-precision GNSS antenna
Taoglas has launched the GVLB208 series, an active and passive dual-band GNSS L1/L5 stacked patch antenna — the first in a new family of ultra-compact antennas.

Combining a tiny package with concurrent L1/L5 support and stable right-hand circular polarization (RHCP), the antennas deliver reliable centimeter-level positioning in a compact 20 x 20 x 8 mm footprint.

The GVLB208 series is designed for applications that require high-precision positioning in a compact form factor. Its size, dual-band support and circular polarization make it suitable for designers looking to improve positioning performance without increasing device footprint.

The new antennas address this challenge with a single-feed stacked patch design that supports concurrent L1 and L5 GNSS bands. By leveraging dual-band operation, they significantly reduce the impact of multipath interference, enabling more reliable positioning and improved accuracy in complex RF environments.

The series delivers dual-band L1/L5 performance typically associated with larger GNSS patch antennas. The antenna achieves peak gain of up to 1.5 dBi, approximately 50% efficiency across both bands, and an axial ratio of around 4 dB, supporting stable RHCP signal reception and consistent positioning performance.

Optimized for major global GNSS constellations, including GPS, Galileo, GLONASS and BeiDou, the GVLB208 series supports reliable operation across varied RF environments.
- The passive GVLB208 A single-feed architecture enables dual-band L1/L5 performance without the complexity of multi-feed designs, while its pin-mount configuration simplifies RF layout and integration. It can be easily implemented on standard PCB designs, with optimal performance achieved on a typical 70 x 70 mm ground plane.
- The active AGVLB208.A, including active electronics and filters, is supplied with 1.13 micro-coax cable and an I-PEX MHF I connector for easy integration with the latest multiband GNSS modules.
The GVLB208 series is suitable for autonomous delivery robots requiring seamless sidewalk navigation and precise drop-offs, where every centimeter counts. It also supports applications including unmanned aerial vehicles (UAVs), telematics systems, fleet and asset tracking, precision agriculture, and industrial IoT deployments.

Taoglas plans to expand the GVLB208 family later this year with an active SMD variant with integrated active electronic components, designed for automated high-volume manufacturing.
May 26, 2026
Seen & Heard: Self-driving cars get smarter, Antarctic Peninsula turns green and more

“Seen & Heard” is a monthly feature of GPS World magazine, traveling the world to capture interesting and unusual news stories involving the GNSS/PNT industry.

Smarter self-driving cars

Photo: hoi dongsu / iStock / Getty Images Plus / Getty Images

Researchers at Drexel University have developed a testing method to enhance the robustness of autonomous driving systems. Their approach uses dynamic visual patterns to evaluate object detection capabilities in self-driving cars, focusing on critical objects such as traffic signs. A “Screen Image Transformation Network” (SIT-Net) simulates real-world image capture scenarios affected by environmental factors. By identifying weaknesses in autonomous vehicle perception systems, the researchers aim to improve safety and reliability in future self-driving technologies.

Robo-dog gets an upgrade

Photo: Boston Dynamics / Leica Geosystem

The Leica BLK ARC autonomous laser scanning module has become the first certified reality capture device capable of being fitted to Boston Dynamics’ robotic dog, Spot. The BLK ARC, when mounted on Spot, is designed for fully autonomous and repeatable scan missions. Users can plan scan paths remotely using existing drawings or BIM models, allowing the robot to navigate and capture data with minimal human intervention. Spot features a 360° vertical and 270° horizontal field of view, with a scan range of up to 25m.

USGS aids recovery after Hurricane Helene

Photo: Logan Combs, USGS

The U.S. Geological Survey (USGS) is actively aiding recovery efforts following Hurricane Helene by collecting flood data, repairing damaged stream gages and analyzing new flood records. The agency has deployed its landslide event team to assess and document landslide impacts, conduct aerial surveys and map affected areas. By collaborating with local, state and federal agencies, the USGS is providing critical data and expertise to support disaster response and recovery efforts.

Antarctic Peninsula turns green

Photo: Tom Roland

Satellite imagery revealed that the Antarctic Peninsula is experiencing a dramatic increase in vegetation, with plant coverage expanding from less than 1 km² in 1986 to nearly 12 km² by 2021. This trend has accelerated significantly, coinciding with extreme heat events and record glacier melting linked to climate change. The study, conducted by researchers from the Universities of Exeter and Hertfordshire and the British Antarctic Survey, indicates that warmer temperatures and increased precipitation create favorable conditions for mosses, which dominate the newly vegetated areas.

December 27, 2024
Swift Navigation, SolarCleano: cleaning robots keep solar power running

A SolarCleano F1A robot tackles a tough cleaning challenge on a solar farm in Saudi Arabia. (Photo: SolarCleano)

SolarCleano, based in Garnich, Luxembourg, makes robots that clean large solar panel installations using GNSS receivers and corrections from Swift Navigation. We asked Christophe Timmermans, SolarCleano’s managing director, a few questions about its technology.

How often do solar panels need to be cleaned?

For decades, it was believed that solar panels did not need to be cleaned due to their angle to the ground and rain. Nowadays, however, the cleaning of solar panels is widely accepted as necessary to optimize a plant’s return on investment (ROI).

How much time per sq. meter do your machines take to clean solar panels?

To provide the fastest possible ROI to our customers, we developed a range of robots to best address the needs of various solar plant layouts. A large utility-scale project with high level of soiling losses in a desert environment will need a very fast and reactive cleaning solution such as our SolarBridge B1, which can clean 24/7/365 fully autonomously. The most suitable solution for a farm rooftop in Germany that needs to be cleaned three to four times a year might be our F1 model, which can clean the equivalent of up to two soccer fields a day. It is designed for rooftops, floating panels and mid-size plants up to 50 MW. While the speed of cleaning is a very important variable, the quality of cleaning is often considered as the driver to performance, which is why we propose different types of brushes depending on the soiling types. Plus, the robot speed can be modified according to the soiling level.

Why do robots need GNSS receivers to clean solar panels?

Moving on inclined, wet glass surfaces makes odometry unreliable because robots might occasionally slip. Therefore, GNSS is the most reliable way to continuously monitor their exact position. Our robots also need path planning because they cannot operate randomly like lawn mowers. Safety is obviously a major concern; we need a very high localization accuracy to ensure that robots don’t fall off the panels. Finally, the largest solar plants are developed in dry, remote locations with high irradiation such as the Sahara, Atacama and Australian deserts. GNSS allows us to have very accurate localization even in those remote areas. In addition, this solution can easily be installed on already-existing solar plants with little capital expenditure.

What spatial accuracy requirements do the robots have for this task?

Safety is our absolute priority. Therefore, our robots need an accuracy of less than 3 cm. They also need to be aware, in real time, of changes in their surroundings, such as maintenance teams, animals and uneven ground.

On large solar farms, GNSS receivers always have a clear line of sight to the satellites and do not suffer from multipath. So, what are the key technical challenges?

Our robots have the additional advantage that they do not need to drive very fast. However, we need to manage fleets of robots on the other side of the world in regions difficult to access and with harsh weather conditions, such as very high or low temperatures and the accumulation of dust behind panels due to air vortices. We need to be able to perform remote maintenance and solve any issue from our control center in Luxembourg. These challenges make our robots increasingly robust. With a current fleet of more than 300 robots around the world, we collect lessons every day to ensure a greater reliability for our upcoming generations of robots.

Why did you choose to partner with Swift Navigation?

We share a vision with Swift: “Accessible automated solutions serving sustainable goals.” We also share other important values, such as “iterate quickly” and “focus on what matters.”

March 31, 2022
How could your tractor be so careful?
Photo: Septentrio

On a French vineyard in the Loire Valley, a tractor is driving between the grape vines with no one behind the wheel. Meet TREKTOR, the autonomous hybrid robot that works tirelessly to weed the organic vineyard producing some of the finest Gamay wine, called Anjou Gamay Village.

After TREKTOR worked the land for a month, its developer, a company called Sitia, reviewed the quality of their autonomous robot’s work. They counted grape vines damaged during operation — two in one month — and approached the farmer to reconcile the liability. To Sitia’s surprise, he responded, “When I use my manual tractor to get the same job done, I damage at least two vines a day! How did your tractor manage to be so careful?” Sitia’s developers thought for a while and then replied, “It’s thanks to the high quality and accuracy of the components that are inside.”

“Despite the strong magnetic field emitted by the generator on the TREKTOR, the AsteRx SB ProDirect receiver did not have any issues,” said Clément Aubry-Tardif, Sitia’s R&D manager. “The spectrum analyzer in its web interface showed other small radio interferences aboard the robot, but everything was still working fine.”

Integrated into the TREKTOR is an AsteRx SB ProDirect dual-antenna receiver, which provides the reliable high-accuracy positioning and heading needed for autonomous operation. Sitia chose the receiver for the following reasons.
- It has centimeter-level accuracy with RTK, which reduces crop damage and increases yields.
- Its heading helps point implements in the right direction. Unlike inertial systems, it’s reliable and accurate even in static or slow-moving applications.
- Built-in advanced interference mitigation (AIM+) technology makes it resistant to radio interference, while its LOCK+ technology ensures robust satellite tracking even under intense vibrations or shocks.
- It includes an intuitive web interface for fast prototyping and easy real-time testing.
Sitia is a French company specializing in autonomous robots. Its TREKTOR helps compensate for the current farmer shortage, which is especially felt on organic farms, where weeding is seven times more labor intensive due to the use of few (if any) herbicides. TREKTOR is a flexible solution that can adjust its height and width on the fly, adapting to various working environments. It can also change implements to perform various functions. Depending on TREKTOR’s dimensions and implements, the distance from the crop to the robot changes, making high-accuracy positioning crucial to minimize damage to any of the crops.
January 31, 2022
Autonomous rubbish robot wins Galileo Masters 2020

Photo: Angsa Robotics

Startup Angsa Robotics was named the overall winner of the Galileo Masters 2020 competition for its autonomous rubbish robot.

According to Angsa Robotics, “Clive” is Germany’s first autonomous rubbish robot. It can move independently and detect and localize individual objects based on its unique artificial neural network architecture, which enables it to clean grass and gravel areas. In addition, individual objects such as crown caps or cigarette butts are targeted for collection, but insects are spared.

The robot’s target use cases include cleaning festival venues after events and the daily cleaning of parks and other green spaces. It can be used where conventional sweeping machines designed for flat asphalt surfaces cannot be used, Angsa Robotics said.

Precise localization via GNSS is essential to its operation, Angsa Robotics added. With better localization, “Clive” can plan a more efficient path and clean a given area faster.

“Angsa Robotics is another concrete example of the innovation and applications that GNSS is enabling for the benefits of business, society and the environment,” said Rodrigo da Costa, executive director of the European GNSS Agency (GSA). “The combination of precise GNSS localization with further state-of-the art techniques such as artificial intelligence and robotics captures in a nutshell the spirit of the three challenges in this year’s edition of Galileo Masters.”

The Galileo Masters’ network of 101 partners from 18 countries focuses on the regional implementation of the competition to ensure a high level of diversity while enhancing both job growth potential and regional development opportunities. At the 2020 Space Awards, seven challenge winners were honored by representatives of the European Commission, GSA, the German Aerospace Center (DLR), and the German Federal Ministry of Transport and Digital Infrastructure.

The Galileo Masters, founded by AZO, DLR and the Bavarian State Ministry of Economic Affairs and Media, Energy and Technology, annually awards the best services, products, and business ideas using satellite navigation in everyday life.

December 11, 2020
Ole Miss students get meals delivered by robots

Photo: Christian Johnson/University of Mississippi

As University of Mississippi (UM) students resume classes for the spring semester, they are sharing the campus’ sidewalks with a fleet of robots that can deliver meals at the push of a button.

Starship Technologies has launched robot food delivery services at the university, the first in the Southeastern Conference to have autonomous delivery robots.

Beginning Jan. 22, Ole Miss students, faculty and staff can access the Starship Deliveries app (iOS and Android) to order food and drinks to be delivered anywhere on campus, within minutes from any of the 30 robots serving UM. The service will work in conjunction with student meal plans.

“Ole Miss Dining is focused on the continued utilization of advanced technology to enrich the student, faculty and staff dining experience,” said Chip Burr, resident district manager of Ole Miss Dining Services. “We are excited about the expansion of our mobile ordering operation and the new opportunities this partnership creates.”

The robots use a combination of sophisticated machine learning, artificial intelligence and sensors to travel on sidewalks and navigate around obstacles. The computer vision-based navigation helps the robots to map their environment to the nearest inch. They can cross streets, climb curbs, travel at night and operate in both rain and snow.

A team of humans also can monitor their progress remotely and take control if needed.

By making food and drink more accessible, the Starship robots save time and reduce stress, aiming to make the busy lives of the Ole Miss community a little easier, Burr said.

Items can be ordered from Starbucks, Chick-fil-A, McAlister’s, Panda Express, Which Wich, Qdoba, Einstein Bros. Bagels, Raising Cane’s, Steak ‘n Shake, Freshii, Papa John’s and Sambazon. After choosing their items, users select their location by dropping a pin on the campus map where they want their food delivered.

The app allows users to watch the robot’s journey in real time through an interactive map. Once the robot arrives, the user will receive an alert and can meet the robot and unlock it through the app.

The delivery usually takes just minutes, depending on the menu items ordered and the distance the robot must travel. The robots can carry up to 20 pounds.

Starship Technologies operates commercially on a daily basis around the world. Its robots have traveled more than 350,000 miles and completed 100,000 autonomous deliveries.

“We’re honored to be able to help make lives a little bit easier for Rebels across the Ole Miss campus by offering the world’s leading autonomous delivery service,” said Ryan Tuohy, senior vice president of business development at Starship. “Whether it’s getting breakfast delivered in the morning or having a late-night snack, our robots are here to serve students, faculty and staff at all times of the day.”

January 27, 2020
Trimble and partners explore using construction robots

Photo: Trimble

Trimble, Hilti and Boston Dynamics are collaborating to explore the integration of Trimble’s and Hilti’s construction-management software solutions, GNSS technology and reality-capture devices with Boston Dynamics’ Spot Robot platform.

Autonomous robots can play a significant role in construction, specifically in production and quality control workflows by enabling automation of routine and tedious tasks, reducing workload and improving safety. The companies will collaborate to develop a “proof-of-concept” solution.

Equipped with Trimble’s and Hilti’s reality capture devices as its payload and directly communicating with a cloud-based construction management application, the Boston Dynamics Spot Robot will be able to provide consistent output, deliver improved efficiency on repeatable tasks and enable up-to-date as-built data analysis.

The autonomous, terrain-agnostic capabilities support the dynamic nature of the construction environment, enabling the robot to bypass obstacles and maintain its defined path to support routine tasks such as daily site scans, progress monitoring, asset management and remote support.

Multi-directional communication between the robot, Trimble’s and Hilti’s payloads and the cloud application support a continuous flow of information and closes the loop for the construction environment.

“Utilizing robots for routine tasks in hazardous environments to improve safety, efficiency, and data capture consistency is part of our digital transformation vision” said Aviad Almagor, senior director for Mixed Reality and Brain-Computer Interface (BCI) at Trimble. “We are excited for this latest collaboration and looking forward to the potential integration of our hardware and software solutions with the Boston Dynamics’ Spot Robot to enhance field-oriented workflows, reduce amount of rework and facilitate on-site tasks.”

“Trimble’s and Hilti’s domain knowledge, market leadership and technologies are a great fit for our robotic platform,” said Michael Perry, vice president of Business Development at Boston Dynamics. “Deploying an integrated solution in the real-world environment doing dirty and dangerous work, before, during and after the construction stage is a common vision for the three companies, which can help drive the transformation of the construction industry.”

November 21, 2019
Autonomous car hits autonomous robot in bizarre collision

In a unique car accident, a self-driving Tesla Model S hit and destroyed an autonomous Promobot, the robot model v4, on Jan. 6 in Las Vegas. The incident took place at 3000 Paradise Road, Las Vegas.

At 7 p.m., the Promobot’s engineers transported robots to the Vegas’s Congress Hall to prepare their booth at the Consumer Electronics Show, being held Jan. 8-11. All the robots were moving in a line. But one of them missed its way and drove to the roadway of the street parking lot.

At that moment, it was hit by a self driving Tesla car.

This video is property of Kevin Jenkinson, via Promobot.

After the clash, the robot was pushed aside and fell. The car continued to move and stopped 50 meters away from the accident. The passenger who was in the car while driving explains that he decided to try the self-driving mode (Full Self-Driving Capability) and chose an idle area for this test.

“There was nobody there, no men, no cars. I switched this Tesla into a self-driving mode and it started to move. And wow! A robot on the track! I thought the flivver would come round, but it bumped straightly into it! I am so sorry; the robot looks cute. And my sincere apologies to the engineers,” said George Caldera, a Tesla passenger.

As a result, the robot suffered serious damage. Parts of the body, the mechanisms of the arms, the movement platform and a head are destroyed. Now the robot is not able to take part in the exhibition and most likely there is no way to restore it.

This video is property of Steven Smith, via Promobot.

“Of course we are vexed. We brought this robot here from Philadelphia to participate at CES,” said Oleg Kivokurtsev, Promobot’s Development Director. “Now it neither cannot participate in the event not to be recovered. We will conduct an internal investigation and find out why the robot went to the roadway.”

The Tesla S reportedly uses the u-blox NEO-M8L GNSS chip. The company also in December 2018 received a patent for more accurate GNSS positioning using other vehicles as reference stations to share raw GNSS data and make positioning corrections.

Promobot is a manufacturer of autonomous service robots for business with development centers in Europe and Asia. Several hundred of Promobot robots operate in 26 countries around the world. They work as consultants, concierges, guides and administrators. At CES, Promobots will meet attendees at the Promobot booth, where it will give dance performances every hour.

The robot victim’s relatives have been notified. (Screenshot from video by Kevin Jenkinson)

January 7, 2019