大疆无人机手势识别 麻省理工研发用手势就能控制的无人机

麻省理工研发用手势就能控制的无人机  

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.
这个操作让人印象深刻，不仅是因为它利用生物反馈控制设备，代替了光学或其他类型的手势识别，还因为控制的精细程度，为这种远程技术创造了一系列潜在的应用方式。
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.