Spring Validation
| Objective |
| 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 |
| Location | NSH |
| Equipment | Base Station, Locobot with an onboard computer (Nvidia Xavier), Realsense D435. |
| Personnel | All 4 team members |
| Procedure |
| PART A: – 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 PART B: – 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 |
| Verification |
| PART A: – 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 PART B: – The planner adapts to changes in the obstacle map and the robot parameters and generates a path that leverages each robot’s capabilities. |