For autonomous vehicles (AVs) to travel safely, they require up-to-date, high-definition maps that accurately reflect their changing surroundings. If not continually revised, these maps quickly become outdated, increasing the risk of accidents and stalling the development of fully self-driving vehicles.&nbsp;Dr. Gaurav Pandey, associate professor in the Department of Engineering Technology and Industrial Distribution (ETID), received a grant from Ford Motor Company to push the boundaries of current technology. &nbsp;At his <a href="https://sites.google.com/tamu.edu/cvrl/">Computer Vision and Robotics Lab</a> in ETID’s Multidisciplinary Engineering Technology program, Pandey is focused on creating the most optimal maps in the most optimal way to make highly and fully automated transportation part of daily life.&nbsp;Some people believe AVs can safely navigate from point A to point B relying solely on cameras, just as humans use their eyes. However, Pandey points out that humans utilize their vision in conjunction with mental maps formed in their minds. These mental maps are automatically updated when conditions change, such as during construction. Today’s mapping technology for AVs is costly and offers no easy way to update in real-time.&nbsp;To advance this technology, Pandey is developing a software framework for crowd-sourced 3D map generation and visual localization from camera data. The crowd-sourced data will come from the cameras and sensors of Ford vehicles already on the road, leveraging information that is automatically being collected instead of employing specialized mapping cars that travel around to gather data.&nbsp;Pandey will use the crowd-sourced data to create new mapping capabilities that allow real-time updates and aid low-cost visual localization. The intent of this technology is to improve autonomous driving and, ultimately, put fully self-driving vehicles on the road.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1736902897726-News-ETID-WhiteCar-10Jan2025.jpg" style="width: 100%px;" class="fr-fic fr-dib">AV mapping vehicles use multiple sensors and cameras. | Image:&nbsp;<cite id="isPasted">Courtesy of Ford Motor Company.</cite>The Society of Automotive Engineers defines six levels of autonomy, from none at level zero to full at level five. Many of today’s new vehicles are level two, offering driver assistance such as self-parking and speed control. Currently sold by only one company, level three vehicles allow the driver to remove their hands from the steering wheel while remaining ready to assist if needed. Level four needs no driver interaction except in some weather conditions. The eventual goal is level five, at which no human intervention is necessary.&nbsp;Predictions vary regarding when level four and five AVs will be available for consumer purchase. While several companies are testing level four AVs on public roads in the U.S., only a few have them in any form of service. Currently their use is limited to driverless taxis in limited geographic areas within large cities. Waymo, owned by Google’s Alphabet, operates AV taxis in the San Francisco Bay Area, Los Angeles County and Metro Phoenix. Amazon’s Zoox carried its first passengers in California last year and announced it will begin testing its robotaxis in Austin and Miami. Other companies are in the testing phase of their driverless taxis.Level four and five vehicles are expected to increase safety for riders, surrounding vehicles, pedestrians and cyclists by eliminating human error. They will give their riders free time to work or relax. As a licensed driver will not be required, they may be of great benefit to those with disabilities that make driving difficult or impossible.&nbsp;Pandey brings over 10 years of experience in AV research to the goal of making self-driving vehicles a common reality in our world. He says we are already witnessing the use of AVs in various controlled environments, such as in mining and ports, in addition to the AV taxis. For him, it is no longer a question of "if" we will see full automation integrated into all aspects of our lives, but rather "when" it will be implemented at scale.

An autonomous vehicle localized within a 3D map. | Image: Courtesy of Ford Motor Company.

Texas A&M University is creating advanced mapping technologies to further the evolution of autonomous vehicles.

Navigating a Safer Path for Autonomous Vehicles

<section id="isPasted">Electric heavy-duty vehicles offer significant advantages, including reduced noise pollution and lower emissions. However, there’s still a disadvantage to overcome – too many heavy-duty electric vehicles (EVs) could overload the grid.In the Department of Electrical and Computer Engineering, Dr. Thomas Overbye, professor, Dr. Jonathan Snodgrass, a senior research engineer, and electrical engineering graduate students Diana Wallison and Lyric Haylow conducted a three-year project to determine how the grid will be affected if heavy-duty vehicles are electrified in Dallas and Houston, leading to more EVs on Interstate 45.&nbsp;“In some cases, it would make sense to switch from a diesel truck to an electric truck, especially if they're just driving in a city, because if those big semis are idling, they're just burning gas. Whereas if you have an electric truck, you can sit there with zero idle,” Snodgrass said.“Real pollutants come out of car tailpipes,” Snodgrass said. “If we can reduce or eliminate that, there would be less smog and more efficiency. It’s also it's just cleaner in general. And imagine if you're able to reduce traffic noise, especially for people who live along the highways.”Traditionally, transportation and electric grid researchers don’t often talk to each other, which makes it difficult to determine how much EVs will stress the grid. &nbsp;To conduct adequate EV simulations, you need reliable models of both the transportation system (for instance, how much people drive, where they drive and what the charging demand is going to be) and the grid.&nbsp;“The problem is that those who model transportation systems oversimplify grid data and those who model the grid oversimplify transportation data,” Snodgrass said. “What makes our work so novel and cutting edge is that we’re looking at them together.”The team partnered with ElectroTempo, a startup spun out of the Texas A&amp;M Transportation Institute and founded by Dr Ann Xu. ElectroTempo works with utility companies to do state-of-the-art EV modeling. They take real transportation data and convert it to EV miles to determine a forecasted load. For example, if 25% of vehicles were replaced with EVs, ElectroTempo could calculate the expected electrical load demand on the grid.</section><blockquote>Real pollutants come out of car tailpipes. If we can reduce or eliminate that, there would be less smog and more efficiency.<cite>Dr. Jonathan Snodgrass</cite></blockquote><section>The firm then passes that data to the research team, and they perform grid simulations to make predictions about the impact it would have on the grid if “x” number of companies electrified their transportation fleets.&nbsp;“Through our partnership with ElectroTempo, we get truck simulation on demand and run it on our grid models,” Snodgrass said. “We can work together to inform companies when they should stay away from electrifying certain fleets because it would be costly or when to work with utility companies to make some upgrades. They could overload the grid if they electrify too many vehicles, or it could be that they should electrify 10% of their fleet for optimal benefits. It's very important to model heavy-duty truck electrification, since it can have a big impact on the grid.”Using simulations and data, the team found that the potential impact to the grid after electrifying heavy-duty vehicles would be moderate, depending on how many EVs companies choose to have and whether they communicate with other companies and their respective utility companies.&nbsp;“It's a tragedy of the commons type of thing, where if each person independently decides they want to add these big loads to the grid and they're not coordinating with each other, it will cause problems for the grid,” Snodgrass said.But what would happen if the grid started getting overloaded with electrified trucks?&nbsp;“Most likely, grid operators would see the warning signs that transmission lines were getting overloaded, and might redispatch generation, which refers to the process of shifting power plant output in response to changes in power grid conditions. This would increase the cost of electricity for everyone. Or they might tell flexible load to back off.”“Another foreseeable complication is that utility companies could be too optimistic and oversubscribe truck charging, meaning there are more trucks than the grid can handle, or too pessimistic and deny all heavy-duty EVs to companies, neither of which is good.”Ultimately, effective communication and collaboration between companies that electrify trucks is crucial to ensure grid stability and decrease noise levels and emissions.&nbsp;“The research that we’re doing here at A&amp;M in collaboration with our utility and industry partners is paving the way for this to happen,” Snodgrass said.</section>

A team of researchers are looking into how the power grid can be affected by a rise in electrifying heavy-duty vehicles.

Charging Forward: The Impact of Electrifying Heavy-Duty Vehicles on the Grid

In this episode, we recap our favorite episodes from 2024!

2024 Recap & 2nd Annual Saucies!

The use of passenger electric vehicles (EVs) is expected to rise to 28% by 2030 and 58% by 2040, globally. The existing supply chain for EV batteries relies mostly on recycling to close the loop to recover critical minerals such as cobalt, nickel, or copper. However, conventional battery recycling methods are energy-intensive, produce significant quantities of greenhouse gases, and lead to large volumes of waste deposited in landfills.To catalyze the transition from a linear to a circular supply chain for domestic EV batteries, the U.S. Department of Energy Advanced Research Projects - Energy (ARPA-E) has announced <a href="https://arpa-e.energy.gov/news-and-media/press-releases/us-department-energy-announces-13-projects-strengthen-domestic" rel="noopener" target="_blank">$36 million for 13 projectsOpens in new window</a> to accelerate technologies and pursue solutions to extend battery life and facilitate repair and reuse to reduce waste.<a href="https://sealionenergy.com/" rel="noopener" target="_blank">SeaLionOpens in new window</a><a href="https://sealionenergy.com/">&nbsp;Energy</a>, a startup company founded by <a href="https://engineering.cmu.edu/directory/bios/jayan-reeja.html">Reeja Jayan</a>, professor of <a href="https://www.meche.engineering.cmu.edu/index.html" rel="noopener" target="_blank">mechanical engineeringOpens in new window</a> and fellow of the <a href="https://www.cmu.edu/energy/" rel="noopener" target="_blank">Scott Institute for Energy InnovationOpens in new window</a>, was selected to receive $1.6 million to develop a low-cost and low-greenhouse gas coating technology that significantly extends battery cycle life. SeaLion Energy’s project, known as TARDIS-J (Tunable Activation &amp; Regeneration in Devices using In-Situ Jamming), will also reduce waste by regenerating “dead” battery cells.Redefining the future of energy storage, SeaLion Energy’s patented innovation also reduces charging times and improves operating safety.“We need to rethink the way batteries are manufactured from the ground up so that every element can be carefully designed, taking into consideration not just cost and performance but also what happens to the battery at end of life,” said Jayan. “When an EV driver wants to upgrade their vehicle, the battery should live on at a grid storage facility to power peoples’ homes; it shouldn’t sit in a landfill.”<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1734397421219-1010-em-sealion-energy.png" style="width: 100%px;" class="fr-fic fr-dib">Each of the 13 ARPA-E funded projects will be managed under the Catalyzing Innovative Research for Circular Use of Long Lived Advanced Rechargeables (CIRCULAR) program.“ARPA-E turns bold ideas into transformative breakthroughs,” said ARPA-E Director Evelyn N. Wang. “We identified the need for more effective alternatives to the current battery recycling paradigm. I look forward to seeing how these CIRCULAR projects develop regeneration, repair, reuse, and remanufacture technologies to create a sustainable EV battery supply chain.”U.S. Congresswoman Summer Lee <a href="https://summerlee.house.gov/posts/rep-lee-celebrates-1-6-million-in-federal-investment-for-circular-battery-innovation-in-pittsburgh">celebrated SeaLion’s&nbsp;</a><a href="https://summerlee.house.gov/posts/rep-lee-celebrates-1-6-million-in-federal-investment-for-circular-battery-innovation-in-pittsburgh" rel="noopener" target="_blank">achievementOpens in new window</a>, “With projects like this, Pittsburgh is proving itself as a national leader in clean technology and sustainable innovation. Federal investments in transformative projects like SeaLion’s TARDIS-J are critical not only to supporting local talent and job creation but also to advancing a sustainable future. This is what it means to invest in our communities—solutions that benefit the people and the planet.”<blockquote>We need to focus on innovations that lead to cost-effective, scalable solutions that prolong battery life and reduce waste.<cite>Reeja Jayan, Professor, Mechanical Engineering</cite></blockquote>With funding and comprehensive support from the Scott Institute for Energy Innovation, <a href="https://engineering.cmu.edu/mfi/index.html">The Manufacturing Futures Institute</a>, <a href="https://www.cmu.edu/swartz-center-for-entrepreneurship/">The Swartz Center for Entrepreneurship</a>, and <a href="https://www.cmu.edu/cttec/">The Center for Technology Transfer and Enterprise Creation</a>, Jayan credits CMU for helping to accelerate the spin-out of her startup company.“I am very grateful for this support,” she said. “I hope SeaLion Energy’s story can serve as a blueprint for the entrepreneurial pursuits of CMU students and faculty.”With climate change no longer just a possibility, but a reality, Jayan believes that everyone who is capable of doing something to mitigate it, should.“Instead of mining entire ecosystems out of existence to collect very limited minerals, we need to focus on innovations that lead to cost-effective, scalable solutions that prolong battery life and reduce waste. By doing so, we can realize a fully circular and domestic EV battery supply chain for the USA.”

SeaLion Energy, a CMU-led startup, received funding from the U.S. Department of Energy ARPA-E to extend EV battery life and facilitate repair and reuse to reduce waste.

Domestic, circular supply chain for EV batteries

Ever wondered how batteries power your gadgets or how metals are refined to their purest forms? The answers lie in the interplay of cathodes and anodes, two simple yet critical components in electrochemistry. This article will delve into their workings, applications, and challenges.


Cathode Anode: The Basics and Applications

In this episode, we chat with Mark Zachos - President of DG Technologies and Automotive Industry expert on all things Onboarding Diagnostics (OBD) - about the evolution of OBD and what the future holds with the EV revolution.

Podcast: Mark Zachos & The Future of Onboard Diagnostics In Cars (Interview)

If you’re in the Northern Hemisphere, Winter is Coming.And if you’re a diehard cyclist, that also means you’re going to face challenges beyond the cold. Bike paths – just like the adjacent roads – can get mucked up with potholes, ice, and (like your driveway) blocked when a snowplow makes an errant dump.In the future, cities will have a new tool at their disposal to help ensure cyclists can have the best thoroughfares possible in the depths of winter. It’s called the Street Smart Robot, and it was designed and built by the InDro Robotics engineering team at Area X.O in Ottawa. We believe it’s a great example of how robotics can help make future Smart Cities safer, more efficient, and more liveable for all of us.It was a complex build from the ground up, requiring a lot of work on Machine Vision and obstacle detection and avoidance. Here’s a sneak peak we released while development was still underway:<iframe width="640" height="360" src="https://www.youtube.com/embed/I1MTJHVsIKA??si=Bw1lA0hTFdqh2x3B&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true">&nbsp;</iframe><h3 id="isPasted">Funding</h3>Research and Development companies like ours are often fortunate enough to receive funding to assist with projects like these. Our concept for the Street Smart Robot caught the attention of the <a href="https://www.ovinhub.ca/" target="_blank">Ontario Vehicle Innovation Network</a> (OVIN). Its <a href="https://www.ovinhub.ca/" target="_blank">website</a> describes the agency as “Ontario’s flagship initiative for the automotive and mobility sector…driving economic development and catalyzing a future that builds safer, cleaner, and more efficient transportation.”OVIN committed $465,000 to the SSR project.<div title="Page 1">“With a world-class innovation ecosystem, Ontario continues to lead in the development of new mobility technologies and solutions,” said Vic Fedeli, Minister of Economic Development, Job Creation and Trade in our <a href="https://indrorobotics.ca/wp-content/uploads/2024/12/InDro-Robotics-Street-Smart-Robot-News-Release.pdf" target="_blank" data-lf-fd-inspected-kn9eq4roawkarlvp="true">news release</a> about the project. “InDro Robotics’ prototype Smart Street Robot represents the best of our province’s cutting-edge tech research and development that is creating solutions for real-world challenges, and we congratulate them on this milestone.”OVIN also weighed in:<div title="Page 1">“Ontario is home to innovators and game-changers that are shaping the future of mobility on the global stage. The growth of multi-modal transportation, combined with weather-related challenges, presents a unique opportunity for Ontario companies to commercialize leading-edge solutions that make our roads safer and travel more efficient,” said Raed Kadri, Head of OVIN. “This groundbreaking technology showcases the unparalleled caliber of Ontario SMEs in addressing significant mobility challenges—and more broadly, the province’s capacity to foster innovation and accelerate their time to market.”&nbsp;<h3>Networking</h3></div>Robots like the SSR require more than just good sensors and compute. They also require an exceedingly reliable 5G network in order to accommodate the dense data throughput required. Here, we partnered with <a href="https://www.rogers.com/" target="_blank">Rogers Communications</a> for networking hardware and technical support.</div><div title="Page 1">“Rogers is proud to work alongside InDro Robotics and OVIN to improve public safety,” said Tom Turner, President, <a href="https://www.rogers.com/business" target="_blank">Rogers Business</a>. “By leveraging the <a href="https://www.rogers.com/business/iot/wireless-private-network" target="_blank">Rogers 5G Hybrid Wireless Private Network</a>, we’re able to help build safer communities through real-time detection and reporting.”Robust, high-speed networks are crucial for Smart Cities – where a multiplicity of interconnected devices will be constantly relaying data. This will be especially true as more connected and autonomous vehicles like the Street Smart Robot start sharing roadways (or bicycle paths) with people and other traffic..“The Street Smart Robot is designed to greatly enhance the safety of bicycle lanes, particularly during winter. InDro is pleased to have partnered with Rogers and OVIN on this endeavour,” says InDro Robotics Founder/CEO Philip Reece.Below: The SSR incorporates LiDAR and 3D depth cameras to help sense its surroundings – and to avoid cyclists, pedestrians and obstacles<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1733845991303-SSR-LiDAR-Units-scaled.jpg.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="SSR LiDAR"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1733846026679-SSR-Depth-Camera-scaled.jpg.webp" style="width: 100%px;" class="fr-fic fr-dib" alt="SSR Depth Camera"><h3 id="isPasted">InDro's Take</h3>This is actually just the beginning of the Street Smart Robot’s journey. This is the prototype version, and we are already looking at ways to further enhance the product prior to commercial deployment. We’ve learned, for example, that while the existing tread locomotion is great for heavy snow and ice that an all-wheel drive wheeled platform will provide greater agility and speed. We are also looking at a smaller and more human-friendly form factor.That being said, our SSR V1 has proven itself for Simultaneous Localisation and Mapping (SLAM), as well as detecting hazards that could cause cyclists problems.“Safer streets for everyone – including cyclists – are part of the Smart City of the future,” says InDro Robotics Founder and CEO Philip Reece. “The Street Smart Robot is an important step along that road.”We’ll have more to say about our Street Smart Robot when we release V2 in the future. So stay tuned – and, if you’re cycling, stay safe.</div>

A new robot to help ensure cyclists can have the best thoroughfares possible in the depths of winter.

InDro's Street Smart Robot Built to Keep Cyclists Safe in Winter

The safety and efficiency of EV charging systems can be enhanced by integrating advanced protection and sensing technologies.

Enhancing EV Charging Safety and Efficiency: Integrating Advanced Protection and Sensing Technologies

The scaled city, located in the basement of Hollister Hall, seeks to improve the performance of emerging mobility systems, such as connected and automated vehicles, by enabling small motorized cars to interact with their environment as well as other vehicles, some of which are piloted remotely by humans. Credit: Noël Heaney/Cornell University

A 20-by-20-foot “smart” city shrunk to 1:25 scale and its fleet of custom-built cars, drones, cameras and virtual reality technology are helping researchers design a better – and safer – future for transportation. 

Mini smart city drives design of safer automated transportation

&nbsp;The Challenge: Addressing E-Mobility’s Compact Performance Challenge&nbsp;As e-mobility infrastructure expands, the need for advanced charging stations has introduced new technical requirements for size, reliability, and flexibility. When <a href="https://abinsula.com/" target="_blank">Abinsula</a> – an innovative company in the embedded systems and IoT solutions space – was tasked with creating a POC for a smart, wall-mounted EV charger, the company’s priority was to balance high-performance with a compact design that could be customized for future functionality.Abinsula’s experience in embedded systems positioned them well to tackle this project, but they quickly realized that most existing market solutions were either too bulky or limited in flexibility. After evaluating several options, they selected the <a href="https://www.arduino.cc/pro/hardware-product-portenta-x8/" target="_blank" rel="noopener noreferrer">Portenta X8</a> from Arduino’s Pro line and combined it with the <a href="https://www.arduino.cc/pro/hardware-product-portenta-breakout/" target="_blank">Portenta Breakout</a> to create a powerful yet compact solution that could be optimized for rapid development.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzMxOTM5MDQyMDc4LTE3MzE5MzkwNDIwNzgucG5nIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" id="isPasted" class="fr-fic fr-dii">Developing a Customizable Solution with Portenta X8Using Yocto for software customization, Abinsula was able to adapt the microcontroller to meet specific application needs while maintaining efficiency and scalability. As Paolo Doz, co-founder and CTO of Abinsula, explained, “The primary challenge was optimizing the resources of the microprocessor while planning for future functionality expansions. We were able to offload some functionalities to the Portenta X8’s onboard real-time microcontroller, ensuring the system could support additional smart features as needed, such as remote communication via 4G/Wi-Fi®.”This approach allowed Abinsula to also integrate a full human-machine interface (HMI) and control software within just one month, a major accomplishment in a field where time-to-market can provide a decisive edge.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzMxOTM5MDY0NDgxLUFCWDAwMDQ5XzAyLnVuYm94LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Efficiency, Reliability, and Scalability for Future Innovation &nbsp;<iframe id="635a948941249700089f8799" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/arduino-portenta-x8?iframe=true" frameborder="0" scrolling="no"></iframe>Abinsula’s success in delivering a complete, compact POC highlights the benefits of leveraging high-performance microcontrollers for e-mobility applications. The <a href="https://www.arduino.cc/pro/hardware-product-portenta-x8/" target="_blank">Portenta X8</a>’s design offered Abinsula access to a powerful processing-to-size ratio, enabling the development of a fully operational charger that met the client’s standards for both functionality and flexibility. The project also benefited from Arduino’s Board Support Package (BSP), which allowed Abinsula to focus on application development without having to start from scratch.&nbsp;Curious to find out more?&nbsp;Read the <a href="https://www.arduino.cc/pro/case-studies-abinsula/" target="_blank">full case study on the Arduino website</a>.

The Arduino Portenta X8 combines high performance and compact form factor.

The growth of e-mobility demands versatile, reliable charging solutions that meet high standards in compact formats. Using Arduino, Abinsula developed a proof of concept (POC) for a wall-mounted, smart EV charger within a remarkable timeframe.

Abinsula: Rapid Development of a Compact EV Charger

In a world where automation dominates the manufacturing sector, one question persists: why aren't robots omnipresent in our daily lives? The answer lies in the intricate challenges of bridging the gap between humans and machines. While robots thrive in structured environments, the unpredictability and complexity of human behavior pose significant hurdles to seamless integration.&nbsp;In Robotican's recent work, we have developed a new way for humans to interact with service robots. A person is talking to a robot and command it to perform series of tasks a spoken language. Such a command can be: "Go forward up until the end of the hallway, enter the room in front of you, ask the doctor to give you the examination files, and come back here". The robot uses a Speech-To-Text engine, to write the command in text, then it applies a specially trained LLM (Large Language Model) to divide the command into sub-tasks. In our example the sub-tasks will be: "move forward, enter the room, ask the doctor, go back".&nbsp; The robot start performing the sub-tasks according to the required order. &nbsp;While moving the robot uses it cameras to "see" the environment in front of it. The frame from this camera goes into an LVM (Large Visual Model) which receives a photo and output text. When the way is clear this LVM will output "move forward", and an action will be: send the robot a navigation way point 10 meters ahead". When say, in our example, a group of people are standing in front of the robot blocking the way. Then the LVM will output "People are blocking the way", and the action will be "ask them to let me pass through". &nbsp;Then a Text-To-Speech engine will say "Excuse me, I'm a robot with an important task. May I please pass through? Thank you.” Then the robot pass and continues its task. This process is repeated until the robot complete its task, or is unable to do it. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1731928237835-%D7%AA%D7%9E%D7%95%D7%A0%D7%94+2+%D7%9C%D7%9E%D7%90%D7%9E%D7%A8+2+%D7%95%D7%95%D7%99%D7%91%D7%95%D7%9C%D7%91%D7%A8.jpg" style="width: 100%px;" class="fr-fic fr-dib">"The answer lies in the intricate challenges of bridging the gap between humans and machines" This is a unique approach of combining TTS, STT, LLM and LVM to allow robot interact with human, and human interact with a robot in a spoken language, while understanding tasks, seeing and understanding the environment around it, and asking people to help the robot conducting its task successfully. Enter Robotican, a pioneering force at the forefront of autonomous robotics, spearheading the charge to revolutionize Human-Robot Interfaces. As a key player in the Israel Innovation Authority's groundbreaking consortium, Robotican harnesses its extensive expertise and recent advancement in AI and Deep Learning to develop innovative solutions that allows robots to navigate amongst people while interacting with them similarly to the way other peoples do.&nbsp;Championing the quest to teach robots to navigate unstructured environments effortlessly, Robotican embarks on a transformative journey empowered by cutting-edge Large Language and Vision Models (LLM &amp; LVM). Leveraging the revolutionary capabilities of these models, Robotican engineers have unlocked the potential to communicate with robots in a language they understand.&nbsp;Omri Eitan, Robotican's AI expert, sheds light on this groundbreaking advancement, stating, "The transformative power of the latest Language Model technology has ushered in a new era of complexity in decision-making and deep contextual reasoning. Tasks once deemed intensive engineering endeavors now undergo fine-tuning, and interactions once artificial now feel natural." &nbsp; With Robotican's innovative approach, robots decode textual or verbal instructions, process visual data using LVM to navigate crowded environments, and seamlessly engage in dialogue with individuals, courtesy of LLM. This paradigm shift not only enhances precision in task execution but also fosters meaningful human-like interactions, paving the way for unprecedented advancements in automation and artificial intelligence.&nbsp;Witness the dawn of a new era as Robotican redefines the landscape of human-robot interaction, propelling automation into realms previously deemed unimaginable. Join us as we embark on this transformative journey, shaping a future where robots seamlessly integrate into every facet of our lives. #RoboticanRevolution #HumanRobotInteraction #AIInnovation #AutomationAdvancements

Ghostrobotics V60 with Robotican's ARK (autonomous robotic kit)  

Pioneering AI-Driven Collaboration: Transforming Social Navigation into daily routine

Unveiling the Future: Human-Robot Interaction Revolutionizes Social Navigation Using AI and Deep Learning

Imagine being a passenger in a self-driving car as the vehicle starts veering off the road. It’s not a faulty sensor causing the dangerous situation — it’s a cyberattack. Hackers can access the deep learning (DL) neural networks at the heart of the vehicle’s computer system, compromising the safety of its passengers, as well as other drivers and pedestrians.&nbsp;Stopping such cyberattacks requires understanding them first, but this can be challenging. Finding a computing system’s exact deep neural network has many roadblocks. They are often proprietary and, therefore, inaccessible to investigators without considerable legal intervention. Another common problem is that they are updated frequently, making it difficult for investigating researchers to access the most current network iteration. But a new tool from Georgia Tech could unlock the mysterious malware on myriad neural networks in everything from self-driving cars to the IMDB entertainment database. AI Psychiatry (AiP) is a postmortem cybersecurity forensic tool that uses artificial intelligence to recover the exact models a compromised machine runs on and discover where the fatal error occurred.“We trust self-driving cars with our lives and ChatGPT with our careers, but when those systems fail, how are we going to investigate them?” said <a href="https://saltaformaggio.ece.gatech.edu/">Brendan Saltaformaggio</a>, an associate professor with joint appointments in the School of <a href="https://scp.cc.gatech.edu/">&nbsp;Cybersecurity and Privacy</a> and the School of <a href="https://www.ece.gatech.edu/">Electrical and Computer Engineering</a> (ECE).AiP can recover the original DL model on both the local network’s memory and the graphics processing unit that trains the network. It can accomplish this without any specific knowledge of the model’s framework, platform, or version. Instead, it recreates the model using what&nbsp;<a>Saltaformaggio</a> refers to as “clues,” or common components in all neural networks. These include weights, biases, shapes, and layers from the model’s memory image — a frozen set of the bits and bytes operating when the model is running normally. The memory image is crucial because it enables AiP to compare it with the model post-attack.“These models often refine their information as they go, based on their current environment, so an attack might happen as a result of an attacker poisoning the information a particular model is learning,” said David Oygenblik, an ECE Ph.D. student. “We determined that a memory image would capture all those changes that occur during a runtime.”\Once the model is recovered, AiP can run it on another device, letting investigators test it thoroughly to determine where the flaws lie. AiP has been tested with different versions of both popular machine learning frameworks (TensorFlow and PyTorch) and datasets (CIFAR-10, LISA, and IMDB). It successfully recovered and rehosted 30 models with 100% accuracy.&nbsp;“Before our research, you couldn't go to the cyber ‘crime scene’ and find clues because there was no technique available to do that,” Saltaformaggio said. “That's what we are pioneering in the cyber forensics lab right now — techniques to get that evidence out of a crime scene.”Tools like AiP will allow cyber investigators to see the whole picture immediately. Solving cybercrimes can help prevent future ones, from safeguarding a user’s data to keeping a car on the road.&nbsp;

New tool AI Psychiatry recovers compromised deep-learning models so researchers can understand what went wrong.

The Sherlock Holmes of AI

Cornell engineers have come up with a solution to a tricky problem: where to install charging stations for electric vehicles so they’re convenient for drivers and profitable for investors.Without abundant and well-placed charging stations, consumers will purchase fewer electric vehicles. Without enough electric vehicle owners, publicly available charging stations won’t be profitable; that means there will be fewer of them.“Improving charging-station infrastructure is essentially the chicken-and-the-egg problem,” said co-author&nbsp;<a href="https://www.cee.cornell.edu/faculty-directory/h-oliver-gao">Oliver Gao</a>, the Howard Simpson 1942 Professor of Civil and Environmental Engineering at Cornell Engineering.The research team found that in urban settings, installing an equal mix of two different kinds of stations – one that charges at a medium speed and another that charges more quickly – and distributing them strategically increases the chances that drivers will use them. And that in turn improves the profitability for investors by 50% to 100%, compared to current random placement strategies.The research, “<a href="https://www.sciencedirect.com/science/article/pii/S0306261924013588">Bayesian Optimization for Battery Electric Vehicle Charging Station Placement by Agent-Based Demand Simulation</a>,” published Aug. 9 in Applied Energy.“Placing publicly available charging stations around cities sounds like a simple thing, but mathematically, it’s actually very hard,” said lead author Yeuchen Sophia Liu, Ph.D. ’22, an operations researcher in Gao’s laboratory.That’s because simple models don’t allow for the complexity of thousands of possible driver decisions, Liu said, not to mention factors like traffic and road characteristics.So the team reached back six decades to use Bayesian optimization, a mathematics strategy that uses past attempts at optimization to inform each subsequent attempt. That results in a much faster and productive analysis. It has become popular in machine learning algorithms.“The Bayesian optimization model algorithm allows us to simulate millions of individual behaviors, while at the same time, find answers efficiently and quickly,” Liu said.The team set up an algorithm that used Bayesian optimization to analyze data from the Atlanta region, home to about 6 million people. They studied the behavior of 30,000 vehicles on more than 113,000 simulated trips, forecasting a variety of commuter traffic patterns.The algorithm found an optimal placement using only 2% of the runtime of existing benchmark methods. “This enables the use of the algorithm on a more complex, real-world scale,” Liu said.The team found that medium speed “level-2” commercial charging stations and direct-current, fast-charging “DCFC” stations serve different needs. Drivers who park for 20 minutes – while running into a grocery store, for example – are likely to choose fast charging spots. But if someone is going to work and parking for several hours, the driver will likely select the level-2 station.In addition, a sensitivity analysis demonstrated that factors such as the size of the battery electric vehicle market, charging preferences and charging price have significant impacts on the optimal placement and profitability of an electric vehicle charging infrastructure project.The findings have important implications, Liu said. In the U.S., according to the paper, eight states have adopted California’s Zero Emission Vehicle program mandate to have at least 3.3 million zero-emission light-duty vehicles – replacing carbon combustion engine cars – on the road by 2025.“Economically strategic placement of charging stations could play a pivotal role in accelerating the transition to zero-emission vehicles,” Liu said.In addition to Liu and Gao, co-authors are Mohammad Tayarani, a visiting scientist in Gao’s lab, and&nbsp;<a href="https://www.cheme.cornell.edu/faculty-directory/fengqi-you">Fengqi You</a>, the Roxanne E. and Michael J. Zak Professor in Energy Systems Engineering in Cornell Engineering. The work was funded by a grant from the U.S. Department of Transportation.&nbsp;

Cornell engineers have come up with a solution to a tricky problem: where to install charging stations for electric vehicles so they’re convenient for drivers and profitable for investors.

Placement strategy key to getting most out of EV charging stations

Imagine driving a car that can communicate with other vehicles and respond to road conditions in real-time. This innovation is exciting but raises serious questions about safety and security. As vehicles become more connected and reliant on advanced technology, the risk of cyberattacks increases.Cybersecurity is now a major concern for automakers, engineers, and technology experts. To help address these growing concerns, SAE is hosting a two-part course on Automotive Cybersecurity.The course is designed to provide attendees with a comprehensive understanding of automotive cybersecurity fundamentals, best practices, and emerging trends. It will cover topics such as cybersecurity standards and regulations, secure vehicle architecture, risk assessment and management, and incident response and forensics.Level 1What: Automotive Cybersecurity Certification: Level One C2105When: May 5 &amp; 6, 2025, Live Online.How: <a href="https://www.sae.org/learn/content/c2105/">Register attendance here</a>.Level 2What: Automotive Cybersecurity Certification: Level Two C2107When: May 19 &amp; 20, 2025, Live Online.How: <a href="https://www.sae.org/learn/content/c2107/">Register attendance here</a>.&nbsp;<h2 dir="ltr">Overview of the Certification Structure</h2>The course is divided into two levels. Each level will provide valuable insights into automotive cybersecurity.<h3 dir="ltr">Level 1 (May 5-6, 2025)&nbsp;</h3>This session is aimed at participants who want to build a strong foundation in automotive cybersecurity. Participants will learn about the current challenges the automotive industry faces as it becomes more connected.&nbsp;The course provides a deep dive into cybersecurity basics, including industry standards like ISO/SAE 21434 and UNECE WP.29. Attendees will also explore risk management, threat assessments, and security engineering principles. This level is ideal for engineers, managers, and auditors looking to understand the core cybersecurity requirements and how they impact vehicle design and safety.<h3 dir="ltr">Level 2 (May 19-20, 2025)</h3>This advanced session will explore more complex cybersecurity topics. Participants will dive into automotive cybersecurity requirements according to ISO/SAE 21434. Key areas include understanding standards, regulations, and planning strategies for cybersecurity management. Participants will also learn about cybersecurity-conscious culture, handling distributed development, and conducting audits and assessments.&nbsp;Additionally, the session covers post-development activities, such as maintaining cybersecurity throughout the product’s life cycle. Practical aspects like tool management, cybersecurity case development, and validation and testing methods will also be highlighted to ensure the comprehensive protection of automotive systems.This level is perfect for those with prior knowledge or experience in the field looking to expand their expertise.Both levels are designed to provide practical, hands-on knowledge that can be applied directly to real-world automotive systems.<h2 dir="ltr"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1730210147827-cyber2.jpg" style="width: 100%px;" class="fr-fic fr-dib"> What Will Be Discussed – Level 1 May 5-6, 2025</h2>The Level 1 session aims to introduce participants to the basic principles of cybersecurity as they apply to the automotive industry. This includes definitions, key risks, and emerging threats that professionals must be aware of.<h3 dir="ltr">Key Sessions Covered</h3>Here is what you will learn at the Automotive Cybersecurity Certification Level One C2105.<h4 dir="ltr">Day 1:</h4><ul><li dir="ltr">Introduction to Cybersecurity in Automotive: The session will start with an overview of the challenges faced by the modern automotive sector due to the increasing automation and networking of vehicles, highlighting the importance of cybersecurity in protecting vehicles from attackers.</li><li dir="ltr">Transformation of Mobility: Exploring how the mobility landscape changes with the rise of connected vehicles and the relevance of automotive cybersecurity in this context.</li><li dir="ltr">Basics of Automotive Cybersecurity: Core goals of automotive cybersecurity, including protection mechanisms, terminologies, and the fundamentals of current cybersecurity strategies.</li><li dir="ltr">Regulatory Landscape: An overview of key global regulations, including upcoming laws, ISO/SAE 21434 standards, and UNECE WP.29, which define the framework for automotive cybersecurity.</li><li dir="ltr">Automotive Cybersecurity Engineering: How the ISO/SAE 21434 standard integrates into engineering practices, providing an understanding of the procedure, terminology, and the relationship between threat assessment and security concepts.</li></ul><h4 dir="ltr">Day 2:</h4><ul><li dir="ltr">Cybersecurity Governance: Analyzing the objectives and requirements for managing cybersecurity in automotive organizations and projects, particularly through the lens of ISO/SAE 21434.</li><li dir="ltr">Lifecycle Cybersecurity: Addressing cybersecurity management throughout the entire vehicle lifecycle—from concept to decommissioning—using practical case studies for illustration.</li><li dir="ltr">Continuous and Distributed Cybersecurity Activities: Participants will explore the ongoing cybersecurity tasks that need to be addressed, even in outsourced or distributed work settings, to maintain compliance and security integrity.</li><li dir="ltr">Practical Exercises and Final Exam: The course will conclude with a summary of key concepts and an exam designed to certify participants with a TÜV SÜD certification upon successful completion.</li></ul>By attending this Level 1 course, participants will understand the challenges and tools available for implementing cybersecurity measures in the evolving automotive world. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1730210157702-cyber3.jpg" style="width: 100%px;" class="fr-fic fr-dib"><h2 dir="ltr">What Will Be Discussed – Level 2 May 19-20, 2025</h2>The Automotive Cybersecurity Level 2 certification (May 19-20, 2025), developed in collaboration with TÜV SÜD, focuses on practical applications and lifecycle management in compliance with ISO/SAE 21434 and other relevant regulations.<h3 dir="ltr">Key Topics Covered</h3>You will learn:&nbsp;<ul><li dir="ltr">Cybersecurity Lifecycle: The role of cybersecurity from product development to post-development, including the implementation and management of cybersecurity processes.</li><li dir="ltr">Standards and Regulations: Participants will explore not only ISO/SAE 21434 but also additional standards such as UN R155 and how these frameworks guide automotive cybersecurity practices.</li><li dir="ltr">Planning and Audits: Detailed guidance on cybersecurity planning, conducting audits and assessments, and ensuring compliance throughout distributed development processes.</li><li dir="ltr">Cybersecurity Case Development: Learn to create and evaluate cybersecurity cases. It is important to justify the security measures taken throughout the product life cycle.</li><li dir="ltr">Post-Development Activities: Managing cybersecurity beyond the development phase, including maintenance, updates, and end-of-life considerations.</li></ul>Participants will leave the session with the tools and methodologies necessary for comprehensive cybersecurity management in the automotive sector and an exam to earn TÜV SÜD certification.<h2 dir="ltr">Benefits of Attending the Certification</h2>Attending the Automotive Cybersecurity certification offers numerous advantages for professionals in the automotive industry. Here are some key benefits:<ul><li dir="ltr">Expert Knowledge and Stay Updated: Gain valuable insights from experienced professionals in the automotive cybersecurity field. Understand the latest standards and regulations in automotive cybersecurity, including ISO/SAE 21434.</li><li dir="ltr">Practical Skills and Certification: Learn real-world techniques that can be applied directly to your work, from secure design to threat management. Upon completion, participants will receive a certificate to enhance their professional credentials.</li><li dir="ltr">Networking: Connect with other professionals in the field to share ideas and solutions. This will help build relationships and share insights with peers facing similar cybersecurity challenges.</li><li dir="ltr">Career Advancement:&nbsp;By earning a certificate of completion, participants can showcase their commitment to professional development and their value to current and potential employers.</li></ul><h2 dir="ltr">Who Should Attend?</h2>This certification is designed for professionals involved in the automotive industry who are looking to deepen their knowledge of cybersecurity. Engineers, product designers, and managers responsible for vehicle safety and cybersecurity will benefit the most.&nbsp;Compliance officers and auditors who need to stay updated on industry standards, like ISO/SAE 21434, will also find it useful. Whether you are new to cybersecurity or have prior experience, this event will help you understand the current threats, regulations, and best practices in automotive cybersecurity.<h2 dir="ltr">Register Your Attendance Now!</h2>The Automotive Cybersecurity certification (Levels 1 &amp; 2) is an important event for anyone involved in the automotive industry. With the increasing number of cyber threats, it is crucial to stay informed and prepared. Attending will give you valuable insights and practical knowledge to help safeguard your vehicles and systems.Register now to secure your spot and be part of the important discussions that will shape the future of vehicle security. Join us in making the automotive industry safer and more secure for everyone!Register now for <a href="https://www.sae.org/learn/content/c2105/">Level 1</a> &amp; <a href="https://www.sae.org/learn/content/c2107/">Level 2</a>!

The Automotive Cybersecurity Certification, organized by SAE International, is a timely event that aims to address these critical issues. The online certification will be held on two separate occasions to accommodate European audiences: Level 1 on May 5 & 6, 2025, and Level 2 on May 19 & 20, 2025.


Automotive Cybersecurity Certification

AI is revolutionizing our ability to train cars to drive safely and to respond to unexpected events. | Shutterstock/Scharfsinn

An authority on autonomous robotic systems talks about the impact of AI on his field here on Earth and growing aspirations for autonomy in space.

The future of autonomous vehicles

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