Three-dimensional computer vision is becoming more prevalent in everyday lives as advances in technology and its accessibility to the general population increase. This type of tech is seen in autonomous driving vehicles, augmented reality (AR), virtual reality (VR) and robotics, to name a few. However, historically, these types of technologies have been limited by their methods employed: LiDAR (light detection and ranging, a remote sensing tech used to measure distances) is limited by its cost and low-resolution to be as useful as it once was in the burgeoning field that is 3D computer vision. Researchers are looking towards something else: vision-based methods using depth foundation models.

Scientists have made major progress in explaining friction, but predicting and controlling it still depends heavily on experiments. A comprehensive review examines the physics-based models behind friction, highlights why friction remains difficult to predict, and identifies key challenges that could make friction control more precise and reliable.

In the fields of material science and engineering, understanding the principles of wear and friction is pivotal for the development and optimization of materials and mechanical systems. A research team has synthesized the current research on wear modeling and friction-induced noises, exploring their mechanisms, influencing factors, and predictive challenges.  By studying wear modeling and friction-induced noise, engineers are better able to predict the lifespans of components and prevent structural failure across a wide range of industries.