For immediate release
indoo.rs GmbH announces their next major release this February, which brings along new features such as the pre-drawn paths for recordings inside buildings with their latest technology, SLAM.
VIENNA, AUSTRIA: indoo.rs GmbH announces their next major release this February, which brings along new features such as the pre-drawn path for recordings inside buildings with their latest technology, SLAM.
indoo.rs has recently launched their SLAM EngineTM, which facilitates and speeds up the process of mapping a building by eliminating most of the manual workload. With their newest release 4.0 from February 11th, indoo.rs introduces an intelligent feature, called the “pre-drawn path”, to further enhance the user experience. In the GPS world this is known as Map Matching.
When doing SLAM recordings in the indoo.rs Mobile Toolkit, which is utilized for mapping a building to enable indoor localization and navigation, users can now apply this new feature to draw the path they need to walk for the recording later. By sketching your paths, it is possible to plan your routes and make sure that every area is mapped. In the ensuing recording process, users just need to walk along the route at a steady pace and make a recording/ground truth at every planned turn.
This new feature brings lots of usability improvements. You no longer have to drag along the map when doing the recording, just calmly walk the pre-drawn path and make the ground truth where it says. Now when you make a ground truth, the phone vibrates so you know the ground truth has been made. Additionally, in case there have been any mistakes during recording, each single step can now easily be corrected and the recording process doesn’t have to be completely restarted.
The pre-drawn path brings three major benefits to the user:
- Increased time efficiency,
- Enhanced usability, and
- Stress free recording
Watch the indoo.rs Quick Guide for SLAM recordings
Besides several bug fixes and stability improvements, the 4.0 release also includes a new Kalman filter, which helps improve the accuracy by 15% on already existing maps