How to use GPS as primary source of data in RTAB-MAP ?

[mrrabbit]

Hi Matlabbe,
I am working on navigating and SLAM for a mobile robot using GPS as localization method. But the problem is, it is failing at some cases due to signal loss at some point in the environment. So I am looking for a SLAM method that does use the GPS as primary source and switched to other slam methods when the GPS goes out of signal and comes back to GPS when the GPS comes back alive. Have any of you guys got any idea about any slam technologies doing this. I tried using RTAB-MAP, but the problem is it uses a combination of all sensors available to it, it does not give priority to GPS as needed. It fuses all these sensor data. Is there anyway to do this.

Thanks for your time.

[matlabbe]

Using a GPS alone may not be enough for localization, is it fused with an IMU? What are the other sensors available?

RTAB-Map uses a Graph-based SLAM approach, in which GPS values are added to the graph as constraints. It needs a least a continuous source of local localization estimation like odometry, then when GPS is not available, it just continues to estimate without those constraints.

Another approach is to fuse odometry with GPS using an EKF filter, like robot_localization package.

In both cases, you need an odometry approach that is able to estimate localization while GPS is not available.

[mrrabbit]

Hi Matlabbe,
There are other sensors like imu, velodyne 3D lidar, intel real sense RGBD camera and garmin_18x gps. I am doing a simulation using all these, How can i use the gps for graph optimization in ros2. There is little documentation for the same(as i have read the wiki github part of rtabmap Robust Graph Optimization). Is there any way that i can configure my launch file to add gps. Is this how we can use GPS for RTAB-MAP. Thank you for your reponse.