running example with the 2_driving_away_filtered.bag data, the ROS node crashes after a short while to an error "Out of Range exeception while optimizing graph: invalid key".
I've tried to increase the smootherLag parameter (default value: 1.5) in config/graph_config.yaml, but it does not seem to fix the issue completely.
I get a same type of error "Out of Range exeception while optimizing graph: Requested variable "x35180" is not in this VectorValues. This happens if the measurement delay is larger than the graph smootherLag..."
I thought to ask if you would have more insight on how to overtcome this problem.
when reading the source code, I found that there are always empty global factors in the "updateActiveGraphAndGetState" function. As for the action, I think the non-linear graph contains only very few factors such as the latest IMU factor or Gnss factor so the isam2 optimizer only consists of a few constraints. What is the reason to empty the buffer?
Hi! In other issure, I see you reply that there is a new version coming soon, I am very interested in it, I want to ask when the new version will be released, or can I get a trial access? Thank you so much!
There is a launch file in graph_msf_ros for compslam_ros. But, I couldn't find your slam in the repo. I want to use your slam i.e., compslam. Is it available? If yes, where can I find it?
Hi, I really like the framework that you proposed.
And I am still waiting for the open-source code to do some researches.
Hope your can release it asap.
Appreciate your work again!
Hello @nubertj ! Thank you for this excellent work. I was a part of the ETH Robotics Summer school and I learnt a lot on using this code to map and localise.
I am currently working on my thesis on a similar topic at the moment and I wanted to ask if this Graph Msf can be used or modified to fuse stereo inertial cameras as well? Is it mandatory to have a LIDAR to use this SLAM method? I remember during the Summer school, since we tested a lot outdoors, the tracking camera gave problems and we disabled it.
My use case for my thesis is to perform indoors, is it possible that I can modify and add an implementation to fuse stereo inertial cameras?
Hello author,
Thanks for sharing the work! I roughly read the paper, if we deploy this dual graph into indoor scene for localization, is it suitable? I think the fallback graph of the paper is consider for gnss drop. In indoor environment, there is no gps, main graph always is active.