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 .
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