Researchers at Huzhou Institute, part of Zhejiang University in China, recently introduced a new approach to robot navigation that is based on a deep neural network and classical optimization ...

Navigating without a map is a difficult task for robots, especially when they can't reliably determine where they are. A new AI-powered solution helps robots overcome this challenge by training them ...

Application of Multi-Modal Fusion in Robot Navigation The core of Chuangzhi Technology's patent lies in the application of multi-modal fusion technology for robot obstacle avoidance and navigation.

The Tri-Fusion positioning system in Mammotion's Luba Mini Vision AWD robot lawn mower promises location accuracy to within ...

Therefore, a method of binocular vision navigation of marine garbage cleaning robot in unknown dynamic scene was put forward. The camera was calibrated to extract the feature points in target image.

Researchers created a deep reinforcement learning model that lets robots adapt to visual changes, maintain localization, and navigate complex indoor spaces more safely and efficiently.

Traditional robot navigation methods either require detailed maps or assume accurate localization is always available—assumptions that break down in indoor or unfamiliar environments.