Keshav Sangam’s Status Report for 2/12/2022

This week was primarily research oriented. My work revolves around processing sensor data, so since LIDAR and mmWave sensors haven’t been delivered, I focused on learning more about the Kalman filter and its various offshoots.  The extended version of the filter works better in non-linear systems, and thus makes sense to use for our purposes. However, in researching sensor fusion techniques, we came across this article that uses a neural network to interpolate the mmWave data for robust mapping. The  network also has additional features such as a radar-based semantic recognizer for object recognition, but it is unlikely we need such features. The final trained network was also found on Github, so we will have to test the efficacy of this network for our robot to see if we could avoid creating, testing, and optimizing an extended Kalman filter. I ordered the mmWave sensor board that was mentioned in the paper, to further maximize the chances that the network could work for us. My progress is on schedule, but it would be extremely helpful if the sensors arrived ASAP so we could work on sensor-Jetson interfacing. I could play around with and test the sensors personally. Deliverables for next week are dependent on whether the senors arrive. If they do, I hope to have the Jetson able to read in both sensors’ data. If not, I will focus on helping Jai with ROS and controlling the robot from the Jetson.