Watch Your Ghost Teach a Robot How to Tag-Team

The technology solves a big engineering conundrum: For humans and robots to truly collaborate, they would have to know exactly what each other is doing.

“Factories currently prefer for humans and robots to work separately because they would need an extremely robust method to sync a human with a robot. That’s not the case for current technology,” Cao said.

With GhostX, whatever plan a user makes with the ghost form of the robot while wearing an augmented reality head mount is communicated to the real robot through a cloud connection – allowing both the user and robot to know what the other is doing as they perform a task.

The system also allows the user plan a task directly in time and space and without any programming knowledge. A YouTube video is available here.

“It’s totally codeless. The user programs the robot by demonstrating in an augmented reality environment how the two will work together,” said Karthik Ramani, the Donald W. Feddersen Professor of Mechanical Engineering.

First, the user acts out the human part of the task to be completed with a robot. The system then captures the human’s behavior and displays it to the user as an avatar ghost, representing the user’s presence in time and space.

Using the human ghost as a time-space reference, the user programs the robot via its own ghost to match up with the human’s role. The user and robot then perform the task as their ghosts did.

GhostX gives the user the option of either planning tasks to be completed at the same time or after each other. The system could also possibly work for planning the tasks of hundreds of robots at once, the researchers say.

The team will next explore the use of GhostX for training other humans.

A patent has been filed for this technology through the Purdue Research Foundation Office of Technology Commercialization. The work was funded by the National Science Foundation under grants FW-HTF 1839971, IIS (NRI) 1637961 and IIP (PFI:BIC) 1632154.

Contacts and sources:
Karthik Ramani,  Yuanzhi Cao, Steve Tally, Kayla Wiles
Purdue University

Citation: GhostAR: A Time-space Editor for Embodied Authoring of Human-Robot Collaborative Task with Augmented Reality Yuanzhi Cao, Tianyi Wang, Xun Qian, Pawan S. Rao, Manav Wadhawan, Ke Huo, Karthik Ramani Purdue University DOI: 10.1145/3332165.3347902