One of only four teams remaining from more than 130 competitors worldwide, our team AURA Foresight is developing autonomous technology to stop wildfires before they grow out of control. AURA Foresight has been selected as a finalist in the prestigious XPRIZE Wildfire Autonomous Wildfire Response competition, emerging as one of just four teams remaining from more than 130 teams from around the world. XPRIZE Wildfire is a four-year, US$11 million global competition designed to accelerate breakthrough technologies capable of ending destructive wildfires. The Autonomous Wildfire Response track, worth US$5 million, challenges teams to autonomously detect, verify and respond to wildfire ignitions across a 1,000 km landscape within just ten minutes. The finals will take place in Nenana, Alaska, where teams will demonstrate their technologies in realistic wildfire response scenarios.

In the aftermath of a devastating earthquake, unpiloted aerial vehicles (UAVs) could fly through a collapsed building to map the scene, giving rescuers information they need to quickly reach survivors. But this remains an extremely challenging problem for an autonomous robot, which would need to swiftly adjust its trajectory to avoid sudden obstacles while staying on course. Researchers from MIT and the University of Pennsylvania developed a new trajectory-planning system that tackles both challenges at once. Their technique enables a UAV to react to obstacles in milliseconds while staying on a smooth flight path that minimizes travel time. Their system uses a new mathematical formulation that ensures the robot travels safely to its destination along a feasible path, and that is less computationally intensive than other techniques.

Cornell engineers have developed a robotic collective that behaves less like a machine and more like a material that flows, reshapes and adapts to its environment without centralized control. The system, called the Cross-Link Collective, consists of dozens of small robots that have limited mobility individually, but together exhibit coordinated and sustained motion. The research, published May 20 in Science Robotics, demonstrates a robotic system that resembles soft matter, continuously deforming and reorganizing as it moves, driven by what researchers call mechanical intelligence. "Instead of relying on explicit computation and communication, the system shifts the intelligence into the shape of the robots and their physical interactions," said corresponding author Kirstin Petersen, associate professor of electrical and computer engineering and the Aref and Manon Lahham Faculty Fellow in the Cornell Duffield College of Engineering. "We're leveraging the contact dynamics to let useful behaviors emerge, so the system naturally settles into configurations that reduce internal stresses and improve motion."

Claire chatted to Edward Mehr from Machina Labs about their RoboCraftsman that shapes complex metal parts for the aerospace, defence, and automotive industries. Edward Mehr is an entrepreneur and engineer specializing in advanced manufacturing, robotics, and artificial intelligence. As the Co-Founder and CEO of Machina Labs, he leads efforts to integrate AI-driven robotics into flexible, on-demand production systems. Under his leadership, Machina Labs is reshaping how industries such as aerospace, defence, and automotive approach metal forming and modern manufacturing. Before founding Machina Labs, Ed worked at leading technology companies, including Relativity Space, Averon, SpaceX, Google, and Microsoft.

You can read the roadmap in full here . Lucy Smith is Senior Managing Editor for Robohub and AIhub. Lucy Smith is Senior Managing Editor for Robohub and AIhub.

Maria Koskinopoulou is an Assistant Professor in Robotics and Computer Vision at Heriot-Watt University. Her research interests include robotic manipulation, perception, robot vision, medical robotics, human-robot interaction, and machine learning. She is involved in major UKRI and EU-funded research projects advancing robotic manipulation, surgical and underwater robotics, autonomous assembly, and waste sorting. Robot Talk is a weekly podcast that explores the exciting world of robotics, artificial intelligence and autonomous machines. Robot Talk is a weekly podcast that explores the exciting world of robotics, artificial intelligence and autonomous machines.

In a paper published in Nature Synthesis, researchers led by Professor Timothy Noël of the University of Amsterdam's Van't Hoff Institute for Molecular Sciences present an advance in autonomous laboratory systems for synthesis optimisation. A versatile, modular design and the option for "human-in-the-loop" analytics, RoboChem Flex caters to all synthesis laboratories, large or small. The paper provides all the information to build their own system. According to Professor Noël, this new version of the RoboChem concept developed by his group will democratise the use of autonomous, sophisticated AI-powered synthesis systems. Such systems are often very expensive, so that only well-funded institutions can afford them.

Claire chatted to Ahti Heinla from Starship Technologies about their AI-powered delivery robots that operate independently on streets and pavements. Ahti Heinla is the co-founder and CEO of Starship Technologies, the world's leading autonomous delivery company building AI-powered robots that operate fully independently in real-world environments. One of the original engineers behind Skype's billion-dollar success, Ahti later made a quiet pivot into robotics, spending the past decade advancing practical, consumer-facing AI. Under his leadership, Starship has completed more than 10 million autonomous deliveries with a fleet of over 2,700 robots navigating streets, pavements, weather, and people, without human intervention. Robot Talk is a weekly podcast that explores the exciting world of robotics, artificial intelligence and autonomous machines.

Consider the chief difference between living systems and electronics: The first is generally soft and squishy, while the latter is hard and rigid. Now, in work that could impact human-machine interfaces, biocompatible devices, soft robotics, and more, MIT engineers and colleagues have developed a soft, flexible gel that dramatically changes its conductivity upon the application of light. Enter the growing field of ionotronics, which involves transferring data through ions, or charged molecules. Electronics does the same, with electrons. But while the latter is well established, ionotronics is still being developed, with one huge exception: living systems.

When assessing the ripeness of fruit, sight and smell can tell you a lot, but the best indicator is often how the fruit feels. Cornell researchers used stretchable fiber-optic sensors to create a soft robot gripper that can predict the ripeness of strawberries by touch, then gently twist them off their branch or vine without causing any damage. The technology, developed in the lab of Rob Shepherd, the John F. Carr Professor of Mechanical Engineering in the Cornell Duffield College of Engineering, could lead to more resilient and ecological food production and increase the availability of fruit species that are difficult to cultivate. Shepherd's Organic Robotics Lab previously demonstrated the potential of stretchable fiber-optic sensors to give soft robotic systems the ability to feel the same dynamic, tactile sensations that enable humans to navigate the natural world. In recent years, the team has expanded into agriculture, designing a soft robotic gripper that injects living plant leaves with sensors that help it detect and communicate with its environment.