- Current Risks and Mitigation
- In our initial testing, running SLAM on the Xavier using the ZED mini had low fps (10). Advaith found that many people have this problem using the default ROS wrapper on the Xavier and had to make modifications.
- We are at risk of going over-budget due to the high cost of high power motors and controllers, and our custom frame. Our mitigation strategy is to look into prebuilt bases and potentially relaxing our requirements to allow for less powerful hardware.
- We did calculations to determine our motor and battery requirements, but the calculations use some assumptions. We use a safety factor of 1.2, but in the case that this was not enough overhead, we would mitigate by relaxing our speed, weight, and battery duration requirements
- Changes to System Design
- Decided on depth cameras over lidar for vision due to budget constraints; we have an Intel RealSense already.
- Schedule Changes
- No changes to our schedule this week.
- Progress Pictures
- 3D map built by the SLAM algorithm
Carnegie Mellon ECE Capstone, Spring 2021 | Michael Li, Sebastian Montiel, Advaith Sethuraman