You might have thought, “what does autonomous mean in robotics?” In the world of autonomy, we not only want technology that is self-sufficient but can learn to grow on its own. Watch the video below as Jason gives a brief overview of what is new at Inertial Sense.

So, what does autonomous in robotics mean? Autonomous means that a robot can run by itself without supervision. To do that is harder than it may seem because it must rely on various types of inputs to know what is going on in the world around it. It then must make decisions based on these inputs.

At Inertial Sense, these are the problems that we are solving. Where we have a lot of experience is combining these inputs in such integrations like an IMU, where we have GPS and inertial sensors that can be combined with autonomous devices. This can be incorporated with such sensors that allow machine learning and visual recognition slam. 

Inertial Sense is currently working on the cloud portion of autonomy. This will allow you to be able to stream a lot of data to the cloud and then improve the machine learning models to improve autonomy more and more. Inertial Sense wants to be able to work with your platform and autonomous devices while increasing its smartness over time.

 

Learn More:

What Does The Autonomous Robotic Landscape Look Like?

How Is The Field Surrounding Autonomous Robotics Advancing?

Autonomous Robotics Videos

 

Video Transcript

Autonomous means that a robot can run by itself without supervision. And to do that is harder than it may seem because it has to rely on various different types of inputs to know what’s going on in the world around it. And then make decisions based on those inputs.

And so those are the problems that we’re solving. And where we have a lot of experience is combining these inputs in an IMU like this, where we have GPS and inertial sensors and such like that. And then we stick it in with machine learning, visual recognition slam. 

And what I’m working on, the cloud portion, we stream a lot of data to the cloud and then improve our machine learning models to improve autonomy more and more over time, so that our platform and our robots get smarter and smarter.