ros – NavAbility

February 21, 2022February 21, 2022

New YouTube video: Easily using camera data for navigation and localization

You have a camera on your robot… but now what?

We’re starting the discussion on how to convert camera data into information that can be used for navigation and localization.

Next up: Loop closures and why that’s the crux of a robust navigation solution!

References:
* Edwin Olson’s AprilTags paper: https://april.eecs.umich.edu/media/pdfs/olson2011tags.pdf
* C/C++ library: https://github.com/AprilRobotics/apriltag
* A Python library: https://github.com/duckietown/lib-dt-apriltags
* Julia library: https://github.com/JuliaRobotics/AprilTags.jl

We’re all learning here, so please feel free to comment about other good wrappers of the AprilTags library!

February 15, 2022February 16, 2022

New YouTube video: Factor graphs and their importance in robotics

We promised to have a conversation on all things robotics, and a great place to start that conversation is on factor graphs. This is the topic of your second video on the NavAbility YouTube channel, which is embedded below.

We also love communication, so If you have a topic in mind please comment on the videos or email us at info@navability.io.

January 26, 2022January 26, 2022

Announcing our YouTube channel on all things robotics!

Announcing our YouTube channel and Livestream on all things robotics!

We’re excited to announce our NavAbility YouTube channel on all things robotics!

We’ll dive into interesting topics about robots, sensors, navigation, and coordination – the “what to expect when you’re expecting a robot” for everyone from commercial users through to home hobbyists. Jim will also be doing a YouTube Live stream to discuss the last video, answer questions, and talk about industry news.

Subscribe the NavAbility YouTube channel to follow us as we release these discussions. We also love communication, so If you have a topic in mind please comment on the videos or email us at info@navability.io.

January 9, 2022March 11, 2022

Conference News: Join us at ICRA 2022 in Philadelphia!

Join Us At ICRA 2022 in Philadelphia

Great news! We’re giving a tutorial workshop at the premier robotics conference, IEEE’s International Conference on Robotics and Automation (ICRA) in Philadelphia.

Join us to learn why navigation robustness is critical in building effective robotics. This is a great opportunity to discuss real-world robotics problems such as the notorious “How do I handle uncertainties in my data?” question, i.e. multi-hypothesis and null-hypothesis data. We’ll also address emerging topics such as SLAM cloud computing and data persistence.

Find our Workshop Landing Page here. See you in Philadelphia May 23rd – 27th!

More to follow! Keep up to date by following us on LinkedIn, join the discussion on Slack, or learn more about our Technology .

November 15, 2021November 15, 2021

Coming soon: Marine surface vehicle example using radar for localization

One of our immediate aims is to demonstrate the NavAbility technology in real-world applications, and in this vein we’d like to give a preview of results from an exciting project.

This example is applicability to a variety of use-cases, from docking marine vehicles through to navigation of industrial indoor robots… And yes, self-driving too.

In the coming weeks we will release this as a complete working example. In the meantime, here is a short overview and preliminary results.

REx and Radar Data

The MITSea Grant Remote Explorer (REx), shown above, is an autonomous marine surface vehicle used for diverse research applications . The vehicle is equipped with a variety of sensors, however the focus of this project is to use only the radar data for localization as it entered the Boston harbor.

Dehann Fourie (CEO) constructed a GPS-denied navigation solution using the NavAbility stack, processing raw ROS radar payloads (shown below) into a complete factor graph to calculate a SLAM solution.

The example demonstrates how specialized data types can be created to capture and process radar information, which is simple to do using the Caesar.jl stack. A preliminary result of the solved trajectory is shown below.

Complete application example to follow soon

Keep an eye out for the complete example in the coming weeks!

Intrigued? Imagine what we can do with your robotics application! Please reach out to us at info@navability.io if you’re curious or have any questions.