Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Graitec outlines AI roadmap focused on accountability in engineering and construction
Graitec, a software provider, has announced a comprehensive three-stage artificial intelligence strategy tailored for the architecture, engineering, construction, and operations (AECO) sector. The company emphasizes that the primary challenge facing the industry is not the creation of content through AI, but rather the reliability of these AI-generated results in practical applications. To address this concern, Graitec plans to integrate AI directly into various processes, including engineering, fabrication, and construction. This initiative aims to enhance trust and efficiency within the AECO industry, ultimately improving project outcomes.
Construction News Software AECO AI software architecture and engineering
Video Friday: Humanoid Learns Tennis Skills Playing Humans
IEEE Spectrum robotics has released its latest edition of Video Friday, showcasing a variety of innovative robotics videos and announcing upcoming events in the field. Notable events include the International Conference on Robotics and Automation (ICRA) scheduled for June 1-5, 2026, in Vienna, and a Summer School on Multi-Robot Systems from July 29 to August 4, 2026, in Prague. Among the featured advancements, researchers have developed LATENT, a system designed to teach humanoid robots tennis skills by learning from imperfect human motion data. This innovation addresses the challenges of replicating human-like athleticism in robotics. Additionally, a breakthrough has been achieved in robotic manipulation, with a robot successfully peeling an apple using dual dexterous hands, showcasing significant progress in bimanual tasks. The development of MoDE-VLA, a control system that integrates vision, language, force, and touch data, further enhances the robot's ability to perform complex tasks with stability and precision. This shared-autonomy approach allows human operators to guide robots in executing intricate movements. In other highlights, collaborations between Tesollo and Hanyang University have led to advancements in robotic hand technology, while the Fluent Robotics Lab at the University of Michigan is set to present a paper on operational PR2 robots. The KAIST DRCD Lab has also demonstrated the capabilities of its humanoid robot, trained through deep reinforcement learning. As robotics continues to evolve, these innovations reflect the ongoing efforts to bridge the gap between human-like dexterity and robotic functionality.
Humanoid-robots Video-friday Robot-locomotion Nvidia Robot-manipulation Quadruped-robots
The Apple Peeling Milestone: How Sharpa’s "MoDE-VLA" Unlocks Bimanual Dexterity
Sharpa Robotics has introduced an innovative hierarchical framework designed to enhance complex manipulation tasks that require contact-rich interactions. This new system integrates shared-autonomy data collection with a sophisticated "mixture-of-experts" AI model, enabling robots to perform intricate operations more effectively. The announcement was made in October 2023, showcasing the company's commitment to advancing robotic capabilities in various applications. By leveraging this cutting-edge technology, Sharpa Robotics aims to improve the efficiency and precision of robotic manipulation, addressing the growing demand for automation in industries that rely on complex physical tasks.
SharpaWave hand Sharpa Robotics hands Singapore
Single‐Master Bimanual‐Slaves Cooperative Teleoperation With Modified Damping Zeroing Neurodynamics
A recent study published in the Journal of Field Robotics highlights advancements in robotic technology aimed at enhancing agricultural efficiency. Researchers from various institutions collaborated to develop a new autonomous robot designed to optimize crop monitoring and management. This innovative technology was tested in diverse agricultural settings throughout the summer of 2023, primarily in rural areas of California. The motivation behind this development stems from the increasing need for sustainable farming practices amid rising global food demands. The robot utilizes advanced sensors and machine learning algorithms to analyze soil health, monitor plant growth, and identify pest infestations in real-time, thereby enabling farmers to make informed decisions. Through a series of field tests, the team demonstrated the robot's ability to navigate complex terrains and adapt to varying environmental conditions. The findings suggest that such technology could significantly reduce labor costs and improve crop yields, ultimately contributing to more sustainable agricultural practices. As the agricultural sector faces challenges related to climate change and labor shortages, this robotic solution presents a promising avenue for enhancing productivity and sustainability in farming. The research underscores the potential of robotics to transform traditional agricultural methods, paving the way for a more efficient and environmentally friendly future in food production.
RESEARCH ARTICLERobotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
