Bastian Solutions produces fully autonomous robots that collect data on their surroundings from Lidars. But in order to obtain a full 360 view, two lidars are used and its data is connected to produce an accurate reading of its surroundings. Currently data coordinates relative to the lidar are picked manually to create a visual viewing of what the robot “sees”. Bastian Solutions has given this problem to Boise State students to come up with an idea to automatically pick these coordinates to visually see what the robot can. Students are to engineer solutions to analyze data and interface to interact with this process. Start with your project statement.
The Bastian Solutions Lidar Data Processing program uses PyQt, a cross platform Gui toolkit, to create the interface through which the user is able to see their autonomous machine's lidar data, construct the hulls for these autonomous machines, and export those created hulls to a format the machines can use for guidance. The program takes in two files, each containing a set of lidar data from a given autonomous machine, and graphs the data in the application. The program can combine these datasets to construct a set of hulls for that machine. This hull is the area that is within a distance from the machine that it uses to regulate its speed when objects get inside of that area. The program is able to export the hulls to a format that can be uploaded to the autonomous machines so they can access the safety fields generated by the program. The hulls generated by the program can also be viewed inside the program to verify their correctness before exporting. Here are some screenshots of the application showing it when first opened, when data is loaded into it, a screenshot of the help menu, and when viewed with dark mode.