A biped robot named Cassie mastered the stairs at Oregon State University with no computer vision or sensors. Engineers taught it to use 'proprioception,' or body awareness-to navigate uneven ...

Behind the intelligent leap of humanoid robots: Sensors become the core hardware, with a market size expected to reach 84.8 ...

The system uses a machine learning technique called attention-based map encoding, trained through reinforcement learning.

A new deep learning model from Cardiff University helps robots choose safer, more reliable paths—marking a shift from acrobatics to real-world navigation.

Instead of pre-loading the robot with a map of its environment, the researchers have developed a navigation technology that enables robots to rely on visual cues when planning their next move.

Researchers created a deep reinforcement learning model that lets robots adapt to visual changes, maintain localization, and ...

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 ...

A team of researchers at the University of Toronto has found a way to enhance the visual perception of robotic systems by coupling two different types of neural networks. The innovation could help ...

Zhongtongfu Information Technology Co., Ltd. recently obtained a patent titled "Robot Vision Line Inspection Navigation Method and Visual Line Inspection Robot," marking an important step in the field ...

Called “Cyclops,” for its single video camera “eye,” the wheeled robotic emulates the quality of visual scenes enabled by current low-resolution implants, performing navigation tasks that may allow ...

How do robovacs navigate? Robot vacuums use a combination of technologies to navigate a home, map its surroundings, avoid obstacles and ensure they cover the entire cleaning area.