Open-TeleVision: Tech boosts robotic control, integrates human intuition with VR

The Open-TeleVision system provides operators with a stereoscopic view of the robot’s surroundings.

Open-TeleVision: Tech boosts robotic control, integrates human intuition with VR

The robot demonstrates its potential to help out at construction sites.

Xuxin Cheng/ YouTube

Researchers from the Massachusetts Institute of Technology (MIT) and the University of California, San Diego (UCSD) have unveiled an innovative, open-source system dubbed “Open-TeleVision.”

While modern developments have provided researchers with large-scale real-robot data, actuation and perception remain a challenge, reports The Robot Report.

Actuation involves controlling the robot’s joints to mimic operator movement. Traditional technology prevents operators from gaining a clear view of the task space. This is a huge limitation in situations where the task is detailed and calls for intuitive views.

The Open-TeleVision system aims to solve these problems by providing operators with a stereoscopic view of the robot’s surroundings while mirroring their own arm and hand movements. The teleoperation system offers a more intuitive way to control robots from afar.

While companies such as Boston Dynamics have showcased autonomous robots more impressive than ever, these systems still struggle to adapt and solve problems creatively— areas where human intelligence thrives.

Robotic capabilities meet human cognition

At the heart of Open-TeleVision is a VR-based interface that streams the operator’s hand, head, and wrist movements to a server. This server then translates these human poses into robot joint positions which control the machine. A single active stereo RGB camera mounted to the robot’s head ensures constant sync with the operator’s head movements.

“The system creates an immersive experience as if the operator’s mind is transmitted to a robot embodiment,” the researchers told VentureBeat.

Our intuition and years of real-world experience have blessed us with the ability to adapt to new and unfamiliar situations. Using our creativity to solve problems adds another benefit.

From lab into the real world

The research team believes that such a human-centered approach to robotics could prove to be invaluable. This is especially the case in scenarios that require nuance or ethical decision-making.

Open-TeleVision could transform a wide range of industries and scenarios. Imagine human-controlled robots navigating dangerous environments while first responders remain safe, responding to disasters. Additionally, skilled surgeons would be able to perform delicate procedures from anywhere in the world, potentially saving more human lives.

According to VentureBeat, the system could benefits even extend beyond the Earth’s atmosphere. Space missions would be free from communication delays that have long plagued missions if astronauts on Earth could control robots on distant planets.

The research team demonstrated the Open-TeleVision system’s prowess over long distances by having an MIT-based team member control a robot located at UCSD. More tests were performed using two humanoid robots: a Unitree H1, and a Fourier GR1, reports The Robot Report.

A bright future and a few challenges

Despite all its promise, several obstacles remain to be ironed out. The research team stressed the importance of further development, particularly in ensuring high-bandwidth connections. This would tackle issues like latency in long-distance communications.

Additionally, the team is also exploring blending their human-control system with AI assistance. They believe that a hybrid system would offer the best of both worlds— human decision-making supplemented by AI’s quick processing capabilities.

The team’s findings were published in the pre-print archive, arXiv.

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Amal Jos Chacko Amal writes code on a typical business day and dreams of clicking pictures of cool buildings and reading a book curled by the fire. He loves anything tech, consumer electronics, photography, cars, chess, football, and F1.

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