This robotics project was selected from the ARM Institute’s 24-01 Technology Project Call, which centered on the following special topic areas: Multi-Modal Inputs for AI Robotics in Manufacturing, Rapid Re-Tasking and Robot Agility, Multi-Robot, Multi-Human Collaboration, and Virtual Commissioning of Advanced Robotic Systems.
Principal Investigator:
ThoughtForge AI
Project Team:
Siemens and Magna International
Description:
In automotive, aerospace, and consumer electronics, adaptive insertion is performed by humans due to the need to apply and adjust force in real-time to successfully insert asymmetrical, oddly shaped objects. A key enabler for the adoption of autonomous adaptive insertion systems is a multi-modal AI that uses real-time information from sensors, combined with novel machine learning (ML) techniques, and new edge computing techniques to adaptively insert parts of varying shapes, sizes, and weights needed for assembling items within different industries. This AI and robotics project seeks to integrate multi-modal AI inputs, ML algorithms, new computing techniques, and sensors into a robotic system that will enable robots to operate flexibly for a broad class of adaptive insertion applications.