Navigating without a map is a difficult task for robots, especially when they can't reliably determine where they are.

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 ...

Researchers from Cardiff University, Hohai University, and Spirent Communications developed a deep reinforcement learning ...

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

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 Narwal Flow is the newest robot vacuum and mop in the company's lineup and its loaded with features for improved mopping ...

3D robot navigation could enable multi-site medical procedures Scientists at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany, developed a novel method for deploying several ...

An approach that uses hours of video and elements of reinforcement learning can guide a robot vehicle almost two miles without a full map of the surroundings.

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 ...