The autonomous stack is part of work with autonomous robotics. In the last 50 years, robotics have come a long way and, use cases for robots are expanding.
From 2019 to 2020 the top 5 areas of robot sales included transportation & logistics, professional cleaning, medical devices, hospitality and agriculture according the International Federation of Robotics (IFR)
If you’re curious about working with robotics or want to learn more about autonomous robotics this article is primer for you.
When humans navigate the world, we use our brain and our senses to process information and make necessary decisions. As autonomous robots are built to navigate the world, they require a combination of processors, sensors, data, and more.
Enter the autonomous stack.
The autonomous stack includes sensors, calibration, mapping, localization, perception, prediction and planning. A whole host of devices, data, and methods to combine the necessary information to make the best decision without human help. For example, autonomous driving vehicles use sensor data, layered mapping data including high definition road information, dynamic data and geometric data, as well as real time data, and object detection (to name just a few). All of this data combine to determine how to drive from point A to point B safely.
Why autonomous robotics?
There’s many reasons to get involved with autonomous robotics. Here are a couple to consider…
There are plenty of use cases on the benefit of robots helping humans. The autonomous driving vehicle aside, there are lots of manufacturing jobs that humans have completed for years that aren’t actually safe to do. We also see application in the medical field as well as. These are two of many industries and intersections where the work of an autonomous robot could increase efficiency, productivity, and support humanity.
See your progress.
As you work on a project, you can literally see the progress you’re making as you build your autonomous robot. This is great if you like to have regular feedback and want to be able see the product of your efforts, be able to adjust and trouble shoot as you go or, just appreciate the gratification of seeing your progress at the end of a hard day’s work.
Contribute to a growing field.
There’s lots of work to be done to adjust the gap between theory and application in this field. By learning the concepts, working on projects and connecting with companies that are focused on autonomous robotics, you’ll be well poised to contribute to research, work and product innovation. For now, AGVs (automated guided vehicles) and AMRs (autonomous mobile robots) are taking up the largest segments of this market.
Some concepts and resources to help you get you started include:
- Kalman filter
- Behavior trees
- Motion prediction
- Deep learning
- This github page from Hima Bindu Maguluri (GHC ’22 Presenter) full of robotics resources.