SimulaMet Receives Funding for Brain-driven remote robotic avatars
Published:
SimulaMet Professor Baltasar Beferull-Lozano awarded grant to conduct foundational research into algorithmic and architectural paradigms enabling remote physical collaboration through brain signals.
The funding comes from the Research Council of Norway for an ICT Renewal project focused on brain-driven remote collaborative physical work, known as DRIVE. The project will be carried out in collaboration with two partners, namely, University of Oslo and University of Texas, Austin.
What DRIVE is trying to do:
DRIVE is creating a system where people can work together physically from different locations mediated by robot avatars. These robots would be controlled by reading brain signals alongside several other multiple sensors, allowing remotely located people to be embodied into robots and interact bidirectionally feeling what the robots are touching, as if they were next to each other.
The main goal:
Let people, regardless of their remote locations, feel like they're actually in close proximity by making sure they can see what's happening and feel physical sensations (touch, pressure, etc.) without noticeable delays, so that physical presence is no longer limited by distance.
The current problem:
Right now, even short distances cause excessive latencies in the network, sensing and computer processing, making it impossible to do precise collaborative physical tasks remotely because the feedback comes too slowly.
Their solution:
DRIVE will create brain-machine interfaces and machine learning algorithms that will exploit brain and motion-tracking signals to predict early enough and with sufficient precision what someone is about to do and track their mental state. The system will use these signals to indicate what the user wants to do next and adjust the robotic control and network resource allocations to make up for the latencies, enforcing embodiment.
The bigger vision:
To enable new ways for people to work together physically across distances, using machines as intermediaries. It would be usable by anyone, regardless of their age, gender, or physical abilities.