|To demonstrate the progress made over the course of this semester in our Hardware Agnostic Path Planner and SLAM subsystem.|
|Requirements||M.F.R.2, M.F.R.3, M.F.R.1, M.N.F.R.1, M.N.F.R.4|
|Elements||Subsystems – SLAM, Planning|
|Equipment||Base Station, Locobot with an onboard computer (Nvidia Xavier), Realsense D435.|
|Personnel||All 4 team members|
– Locobot is placed at the start of a predefined trajectory that it will follow using teleoperation.
– The SLAM subsystem is started, and we move the robot along the predefined trajectory
– The SLAM subsystem would generate the map incrementally, which will be visualized on the ground station computer in real-time.
– Additionally, we will visualize the trajectory calculated by the SLAM subsystem’s localization module, alongside the ground-truth trajectory on the ground station computer in real-time
– At the end of the trajectory, we will also calculate and show the relative pose error in translation and rotation
– We will have a set of predefined obstacle maps in a simulator/visualizer
– We will also have a set of robot parameters representing different types of robots.
– We will run our hardware-agnostic path planner with combinations of these obstacle maps and robot parameters
– We will then visualize the path generated by the planner for each of these combinations
– The SLAM subsystem would generate an HD map of the area that the robot covers.
– The localization module’s relative translational pose error is less than 15 cm, and the relative rotational pose error is less than 10 degrees
– The planner adapts to changes in the obstacle map and the robot parameters and generates a path that leverages each robot’s capabilities.