MIT muscle-control system for drones lets a pilot use gestures for accurate and specific navigation

Darrell Etherington

MIT's Computer Science and Artificial Intelligence Lab (CSAIL) has released a video of their ongoing work using input from muscle signals to control devices. Their latest involves full and fine control of drones, using just hand and arm gestures to navigate through a series of rings. This work is impressive not just because they're using biofeedback to control the devices, instead of optical or other kinds of gesture recognition, but also because of how specific the controls can be, setting up a range of different potential applications for this kind of remote tech.

This particular group of researchers has been looking at different applications for this tech, including its use in collaborative robotics for potential industrial applications. Drone piloting is another area that could have big benefits in terms of real-world use, especially once you start to imagine entire flocks of these taking flight with a pilot provided a view of what they can see via VR. That could be a great way to do site surveying for construction, for example, or remote equipment inspection of offshore platforms and other infrastructure that's hard for people to reach.

Seamless robotic/human interaction is the ultimate goal of the team working on this tech, because just like how we intuit our own movements and ability to manipulate our environment most effectively, they believe the process should be as smooth when controlling and working with robots. Thinking and doing are essentially happening in parallel when we interact with our environment, but when we act through the extension of machines or remote tools, there's often something lost in translation that results in a steep learning curve and the requirement of lots of training.

Cobotics, or the industry that focuses on building robots that can safely work alongside and in close collaboration with robots, would benefit greatly from advances that make the interaction between people and robotic equipment more natural, instinctive and, ultimately, safe. MIT's research in this area could result in future industrial robotics products that require less training and programming to operate at scale.