Intel develops advanced simulation solutions to help bridge the gap from virtual to real-world environments for off-road vehicles.

Typically, when AI is presented with a scene of cluttered objects, the system will try to identify each item based only on its visible parts.

Collaborative solution to provide both the machine vision computing and software platform developers need to build and deploy mobile robots.

While companies are developing robots for specific purposes, Sanctuary is creating a general-purpose robot with human-like intelligence.

The Rodney AI²PA by Barossa Valley Brewing will be available for limited retail sale from mid-January 2022.

The patent clearly outlines the new functionality helps Simbe on its path to commercializing fresh food tracking and management.

Improving the Soil Property and Object Classification will save NASA scientists time when planning routes for their rovers and in finding important formations.

Formerly known as Cartica AI, Autobrains is developing its modular Cartex driving platform for Level 1-4 autonomous vehicles.

The Covariant Brain is a “universal AI that enables robots to see, reason, and act autonomously in the real world.”

OpenAI disbands its robotics research team due to lack of large enough data sets to effectively generate reinforcement models.

Neurala’s VIA software helps manufacturers improve quality inspection on production lines.

Kami will strengthen Embodied’s Moxie robot by adding memory of past conversations context, consistent personality, common sense reasoning.

Goldberg on Ambi Robotics’ Sim2Real technology, how Dex-Net is powering its robots, lessons learned over the years, and the challenges of universal grasping.

Ambi Robotics, formerly known as Ambidextrous Laboratories, raised $6.1 million in seed funding for its picking robots and operating system that are based on simulation-to-reality artificial intelligence (AI). Co-founded by the great Ken Goldberg, a professor at UC Berkeley, Ambi Robotics said it is exiting stealth mode, although its work on improving robotic grasping hasn’t…

Researchers studied how reinforcement learning enabled a robot arm equipped with a parallel jaw gripper and tactile sensors to insert unknown objects into a hole.

There are some tasks traditional robots – the rigid and metallic kind – simply aren’t cut out for. Soft-bodied robots, on the other hand, may be able to interact with people more safely or slip into tight spaces with ease. But for robots to reliably complete their programmed duties, they need to know the whereabouts…

Training data is collected in Unity and used to train a deep neural network that predicts the pose of a cube. This model is then deployed in a simulated robot pick-and-place task.

Artificial intelligence (AI) remains a major buzz word across many industries, including manufacturing, with the media covering new AI capabilities and trends playing a key role in enabling the digitalization of production. But what’s the real story? In many cases, AI exists only in theory, and there’s a long way to go before it’s ubiquitous.…

Researchers said the optical neuromorphic processor could benefit autonomous vehicles and other data-intensive applications.

NVIDIA said its Isaac Gym simulation software is designed to provide end-to-end reinforcement learning for robotics developers.

Phoenix Instinct, one oof the five finalists in the Mobility Unlimited Challenge run by the Toyota Mobility Foundation and Nesta Challenges,

Sierra Ventures and Orbital Ventures have led the $10.75 million Series A financing round for Akasha Imaging, which is developing deep imaging technology to help robots see fine details.