This Project was selected from the ARM Institute’s 23-01 Technology Project Call that addressed the following topic areas:
- Automated Robotic Task Planning
- Multi-Robot, Multi-Human Collaboration, Task Sharing & Task Allocation
- Safe and Scalable Manufacturing of Energetics
- Artificial Intelligence (AI) in Robotics for Manufacturing
- Discovery Workshops and Market Studies
Project Team:
Siemens (Principal Investigator), University of Southern California
Topic Areas Addressed:
Safe and Scalable Manufacturing of Energetics
Description:
This project seeks to automate the manipulation of granular and paste-like materials with robotics to augment human operators for common handling tasks such as scooping and pouring precise amounts without spillage, including those used in the manufacturing of energetic materials. The outputs of this project can also be applied for use in the pharmaceutical and chemical industries. The team will develop a robotic skill based on AI imitation and reinforcement learning to more safely scoop precise amounts of granular and paste-like materials. This will lead to greater versatility by enabling robots to operate in a flexible way in a broad class of manipulation applications, making them easily reconfigurable to adapt to a different process at lab scale and in production. The project will also require little time to deploy and re-purpose by reducing programming, training and calibration efforts through machine learning and AI.