New algorithms will transform the foundations of computing
New algorithms will transform the foundations of computing
New algorithms will transform the foundations of computing
New algorithms will transform the foundations of computing
New algorithms will transform the foundations of computing
New algorithms will transform the foundations of computing
A simple sponge has improved how robots grasp, scientists from the University of Bristol have found.
New algorithms will transform the foundations of computing
-Automate 2023 set record attendance with more than 30,000 registrants
-Automate is heading to Chicago in 2024 and will return to Detroit in 2025
If the OEM uses well-designed, proven components, the mobile platform will provide many years of service, handling cumbersome, heavy loads efficiently with minimal downtime for maintenance.
A research collaboration between Cornell and the Max Planck Institute for Intelligent Systems has found an efficient way to expand the collective behavior of swarming microrobots: Mixing different sizes of the micron-scale 'bots enables them to self-organize into diverse patterns that can be manipulated when a magnetic field is applied. The technique even allows the swarm to "cage" passive objects and then expel them.
Our newsfeeds are filled with talk about the rapid rise of artificial intelligence (AI) in software such as ChatGPT and Stable Diffusion, which can quickly—albeit haphazardly—generate works such as essays and photographs from a text prompt. Reading these, you might be excused for thinking that writers and photographers are soon to go the way of the elevator operator, automated out of existence.
Learning from one's past mistakes is not limited to humans. Computers do it, too. In industries, this is done via computer-based control systems that help operate production systems. For industrial robots that perform specific tasks in batches, say producing clothing, computer chips, or baked goods, the most commonly used control technique is iterative learning control (ILC). Most industries still rely on ILC systems that use a learning strategy called the proportional-type update rule (PTUR). This technique improves the performance of ILC systems by repeating the same task over and over and updating its control input based on errors encountered in previous iterations.
Many existing robotics systems draw inspiration from nature, artificially reproducing biological processes, natural structures or animal behaviors to achieve specific goals. This is because animals and plants are innately equipped with abilities that help them to survive in their respective environments, and that could thus also improve the performance of robots outside of laboratory settings.
The Un-carrier helps Valmont capture mission-critical data in industry-first beyond visual line of sight (BVLOS) drone inspection operation