CERN and the UK Atomic Energy Authority have built PipeINEER, a 3.7-centimetre-wide robot that inspects the Large Hadron Collider from inside. It travels up to six kilometres on one charge, uses AI to spot damage, and reports exact problem locations. The robot saves time and money by avoiding lengthy dismantling of the 27-kilometre accelerator.
Roboticist Benjie Holson created the Humanoid Olympic Games thinking home robots were 15 years away. Within months, Physical Intelligence completed 11 of 15 challenges using vision-only systems. The robots now fold laundry, spread peanut butter, and use dog poop bags. Holson admits he underestimated camera-based learning and has released harder tests.
China has developed its first exoskeleton robot for mine emergency rescue. Built by CHN Energy and the China Coal Research Institute, the system helps workers carry up to 80 kilograms while reducing energy use by 20 percent. The robot has completed three rounds of training with a national rescue team and shows strong stability underground. It marks a step toward human-machine collaborative rescue operations.
Engineers at the University of Southampton created a shape-shifting robotic wing inspired by birds and fish. The soft wing senses underwater currents and adapts automatically, reducing sudden jolts by 87 percent compared to rigid drone wings. It uses less energy and responds faster than existing designs, bringing underwater robots closer to the agility of living animals.
Toshiba Corporation and MIRISE Technologies Corporation have achieved the world’s first deployment of a quantum-inspired optimization computer inside an autonomous
Scientists in South Korea have developed a fully automated catalyst testing system that replaces manual laboratory work with robotic precision.
Agility Robotics Inc. has signed an agreement with Toyota Motor Manufacturing Canada (TMMC) to deploy its humanoid robot across the
Boston Dynamics’ robotic dog is quietly transforming the way aircraft components are inspected at ST Engineering MRAS. In a sprawling
Researchers from the Singapore-MIT Alliance for Research and Technology have developed an AI control system that helps soft robotic arms learn multiple tasks at once and adapt instantly to new conditions without retraining. The system, tested on two physical platforms, reduced tracking errors by over 44 percent and maintained 92 percent accuracy during disturbances. This brings soft robotics closer to real-world use in healthcare, assistive devices, and manufacturing.
A coder’s attempt to steer his robot vacuum with a PlayStation controller has uncovered a sweeping security flaw that exposed
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