I am working on SLAM for autonomous car like vehicles with 2D lasers and IMU (deriving odometry).
I would like to know how efficient is using the existing SLAM algorithms (for example: gmapping in ROS based on rao blackwellized particle filter).
till now i find MAP are high in volume and speed of vehicle is high and most importantly computational time compared to Mobile robots.
Are there any other important factors to consider for car like vehicles in using SLAM algorithm.