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One of the biggest challenges in combating air pollution is reliable, scalable monitoring infrastructure, which remains expensive. Robots can help solve this issue and make air pollution tracking easy, accessible and accurate.

Soft machines—a subcategory of robotics that uses deformable materials instead of rigid links—are an emerging technology commonly used in wearable robotics and biomimetics (e.g., prosthetic limbs). Soft robots offer remarkable flexibility, outstanding adaptability, and evenly distributed force, providing safer human-machine interactions than conventional hard and stiff robots.

Throughout industrial manufacturing, distribution, and logistics the lead time from many AGV manufacturers is more than a year. That means product ordered in Q1 2022 will not be delivered until the following year.

A whole generation of gripping robots has been developed using a design concept originally known from fish fins. An international research team from Biomechanics, with participation from Kiel University (CAU), led by the University of Southern Denmark (SDU), has now optimized this gripping function inspired by insects and challenged this standard in robotics. They also transferred it from hand to foot elements for the first time. This would not only allow robots to grip better with less energy, but also to walk better on uneven surfaces. The findings were published in the journal Advanced Intelligent Systems and as the cover story of the current print issue.

Explore what is neural architecture search, compare the most popular,SOTA methodologies and implement it with nni

A robot has performed laparoscopic surgery on the soft tissue of a pig without the guiding hand of a human—a significant step in robotics toward fully automated surgery on humans. Designed by a team of Johns Hopkins University researchers, the Smart Tissue Autonomous Robot (STAR) is described today in Science Robotics.

In Jimmy Wu's apartment, a scrum of mini robots bump, swerve, and zip chaotically across a tabletop. It looks like an aggressive bumper car rally, but within a few minutes, order emerges.

Whilst initially a temporary measure to resolve manpower shortages and high employee costs, many companies are now investing in smart robotics as a permanent and long-term measure in a post-pandemic world.

Engineering researchers from North Carolina State University have demonstrated a new type of flexible, robotic grippers that are able to lift delicate egg yolks without breaking them, and that are precise enough to lift a human hair. The work has applications for both soft robotics and biomedical technologies.

In this episode, Audrow Nash speaks to Matt Robinson, Program Manager for ROS-Industrial Americas at the Southwest Research Institute. ROS Industrial is a group that seeks to help industrial users, for example factories, leverage ROS and its ecosystem. In this conversation, they talk about Matt’s background, the need for the ROS-Industrial group and what problems they’re working to solve, ROS-Industrial’s consortium, and ROS-Industrial’s new working group.

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Jakob Foerster an accredited Machine Learning Research Scientist who has been at the forefront of research on Multi-Agent Learning speaks with interviewer Kegan Strawn.

Dr. Foerster explains why incorporating uncertainty into multi-agent interactions is essential to creating robust algorithms that can operate not only in games but in real-world applications.

Jakob Foerster
Jakob Foerster is an Associate Professor at the University of Oxford. His papers have gained prestigious awards at top machine learning conferences (ICML, AAAI) and have helped push deep multi-agent reinforcement learning to the forefront of AI research.

Jakob previously worked at Facebook AI Research and received his Ph.D. from the University of Oxford under the supervision of Shimon Whiteson. During his Ph.D., Jakob also interned at Google Brain, OpenAI, and DeepMind.

Jakob’s research interests span Deep Multi-Agent Reinforcement Learning, Human-AI Coordination, Emergent Communication, Search, Planning, and Game Theory.

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After 10 years’ existence, Naïo Technologies is consolidating its status as the agricultural robotics leader by being the first company in the world to certify that its large scale agricultural robots will be operating unsupervised in fields from the spring of 2022!

Through manipulation, a robotic system can physically change the state of the world. This is intertwined with intelligence, which is the ability whereby such system can detect and adapt to change. In his talk, Tamim Asfour gives an overview of the developments in manipulation for robotic systems his lab has done by learning manipulation task models from human observations, and the challenges and open questions associated with this.

Bio: Tamim Asfour is full Professor at the Institute for Anthropomatics and Robotics, where he holds the chair of Humanoid Robotics Systems and is head of the High Performance Humanoid Technologies Lab (H2T). His current research interest is high performance 24/7 humanoid robotics. Specifically, his research focuses on engineering humanoid robot systems integrating the mechano-informatics of such systems with the capabilities of predicting, acting and learning from human demonstration and sensorimotor experience. He is developer and the leader of the development team of the ARMAR humanoid robot family.

You have probably seen one flying above you at some point: a quadcopter, also known as a drone. These flying robots are becoming increasingly important in today's society, leading to stricter demands on their performance in terms of speed, accuracy, reliability and robustness. In order for these demands to be met, improvement of existing estimation and control algorithms is of crucial importance. In his research, Ph.D. candidate Alex Andriën has improved upon several existing methods for estimation and control of quadcopters by employing optimization-based techniques. He will defend his thesis on Monday 24th of February, 2022.

By combining 3D vision, artificial intelligence, and Soft Robotics' industry-proven, IP69K-rated, soft grasping, mGripAI provides industrial robots with the hand-eye coordination of human workers.