We have been field testing this whole week, trying to get consistent deliveries across campus. This is our biggest problem now, the GPS sensor is erratic, which causes our heading to change, which makes our robot go into the grass and get worse localization.
Our biggest problem is localization. GPS has been inconsistent, but surprisingly has worked well a few times. I still think it is worth doing it, but we are working on some mitigation plans for a backup.
Jumps in the GPS cause the controls to go haywire. We mitigated this by moving things into a continuous odom frame, but we found little difference. we think the error lies elsewhere and need to go through recorded datasets to discern it.
Mitigation plan 1: try sidewalk following using some basic feedforward into the controls. Still yet to try this
We tried the roof of the East Campus Garage, and had some GPS errors there. We may try again after analyzing the data from that run.
Worked with michael on the data association, this works well with multiple pedestrians. The perception part of our project is done now.
Progress:
/not much progress from last week, we are still field testing and working out our kinks in our local planners
Next week’s deliverables:
Make sure the robot drives properly
Localization
mitigation plan: do everything in the odom frame and hardcode the map