As smart manufacturing upgrades to flexibility and precision, factory robotic arm target grabbing is the core link of material transfer in the production line, and its performance directly determines ...

Data are needed on the effect of oxygen delivered through a high-flow nasal cannula, as compared with standard oxygen therapy, on intubation and mortality in patients with acute hypoxemic respiratory ...

ABSTRACT: Surrogate-assisted evolutionary algorithms are widely used to solve expensive optimization problems due to their high search efficiency. However, a single model struggles to fit various ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

While the creation of this new entity marks a big step toward avoiding a U.S. ban, as well as easing trade and tech-related tensions between Washington and Beijing, there is still uncertainty ...

As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...

For the low efficiency and poor generalization ability of path planning algorithm of industrial robots, this work proposes an adaptive field co-sampling algorithm (AFCS). Firstly, the environment ...

Getting a handle on LeetCode can feel like a big task, especially when you’re starting out. But with the right approach and tools, it becomes much more manageable. Python, with its clear syntax and ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Abstract: To address the issues of low search efficiency, rough paths, and insufficient computational efficiency in the RRT algorithm, this paper proposes a gravity-guided RRT-Connect path planning ...

An exclusive excerpt from Every Screen On The Planet reveals how the social media app’s powerful recommendation engine was shaped by a bunch of ordinary, twentysomething curators—including a guy named ...