This week I drew out the block diagram and implementation details for our project. First, we decided to localize the person on the same frame of reference as the camera by using Ultra Wideband (UWB) instead of IMU to avoid drifting. I did some research on UWB models and came across DWM1000 which seems suitable for our use case. We put 2 in the order list so we can start testing them next week. With 2 anchors in the room, we figured out a way to locate the coordinates of the person. I also did some research on the stereo camera mounted on the wall. We decided on the stereo camera dual OV2311, since it provides depth perception and is also compatible with the Jetson. We will also set up the Jetson and start running certain libraries on the input images next week. We decided to use the OpenCV library to convert from stereo images to a 3D point cloud, and Open3D to convert from the 3D point cloud to a 2D occupancy matrix. We looked into these libraries and it seems appropriate for our use case. We also decided to use the D* path finding algorithm. This algorithm tracks updates continuously and gives future directions. With these high level implementation details ironed out, we also spent some time making the design presentation slides for next week. I believe our progress is on schedule.
Next week, we first plan on setting up the Jetson Nano. This in itself will take up some time. After we set it up, we would like to run the stereo camera on the Jetson and take some input images. We could try setting up the camera on the ceiling and see how it could classify images from the bird’s eye view. However, the priority is definitely setting up the Jetson and connecting it to the camera module.