An open source approach to physical AI from Intrinsic

Deborah Lupton / Pop Chips / Licenced by CC-BY 4.0

Intrinsic (an AI robotics group at Google) announced that the company is making parts of its platform open source. Intrinsic Core™ is a set of ROS-compatible capabilities for building sophisticated robotic applications.

The capabilities included in the open source package are as follow:

• Intrinsic Control. A hardware-agnostic, real-time control framework that delivers sensor-based control. It allows the robot to dynamically adapt its behavior mid-trajectory based on changes in the environment. It is designed to deliver efficient, collision-free paths. The idea is that users can swap out different robot arms, grippers, sensors, and more without needing to rewrite drivers.
• Pose estimation. Provides an accurate six degrees of freedom pose estimation of 3D parts.
• Motion planning. Logic auto-generates efficient paths while avoiding collisions.
• Grasp planning. Designed to enable various grippers to automatically and dynamically adapt to the location and orientation of a part and grasp it with a higher probability of success.
• Simulation services. These aim to provide a straightforward way to test and troubleshoot robotic solutions that update as you build.
• Camera calibration. Automates how a robot’s camera can be calibrated and physically aligned
• Intrinsic-ROS drivers. Pre-configured, ROS-compatible drivers for supported robots, grippers, and 3D cameras.

Alongside this package, Intrinsic has also released Open Machine Tending Solution (OMTS). This is a ready-made reference design for a real-world use case. The intention is to give developers a starting point to customize their own solution, without needing to build from scratch.

You can download Intrinsic Core on GitHub here.

Lucy Smith is Senior Managing Editor for Robohub and AIhub.

Lucy Smith is Senior Managing Editor for Robohub and AIhub.