PR1 goals (Completed)

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Overall system logic, member contributions, and mechanical integration.

PR2 Goals (Completed)

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1. Integration of patient pose algorithm, deploying the current post estimation algorithm developed by Airlab on the Jetson Orin, designed to analyze and extract head and chest orientation. Its performance will be evaluated against active benchmarks on both time and confidence metrics.
2. Autonomous take off, landing and return to base lanner integrated as part of objectives within the behavior tree within MAVROS,
3. Gimbal control, in terms of a ROS node that is subscribing to requested gimbal angles as desired by the algorithm either searching or locking onto a patient. Integration with Gremsy SDK to achieve a designed Roll-Pitch-Yaw of the gimbal. ROS publisher, sending back the active gimbal angles.
4. Camera control. ROS subscriber: requested zoom level; ROS publisher: Current zoom level (may include current frame as image and current camera intrinsic parameter as well).
5. IssacSim Pipeline – simulated version of our drone within a test environment, testing takeoff, landing, and behavior tree planner, alongside complex motions to iterate on algorithms prior to deployment to drone.
6. Behavior Tree Hierarchy Draft. Change modes based on many factors. Modes should at least include: Armed/Disarmed, Takeoff, Landing, Emergency Stop, Return to launch, Initial Mapping, Searching casualty, Inspecting casualty.

PR3 Goals (completed)

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1. Drone System Monitor, Foxglove version, required for single operator usage to monitor both video streams and single-click actions
   1. Fully Integration Path Planner for Mapping the Geofence Zone; this allows us to perform a search over the entire competition area, identifying and locating patients rapidly.
   1. Triage Data Collection from Test Flight: Mock scorecard/algorithm system that collects streaming data from drone overflights, to then be used to train the next iteration of algorithms to improve competitive accuracy
2. Auto Flight Tests with all integrated components (Path Planner for Mapping the Geofence Zone,  Local Search of Patient Planner, Patient Detection Algorithm, and Patient Pose Estimation).
3. Fully Integrate Local Search of Patient Planner with Behavior Tree and Patient Detection Algorithm.
   1. Patient Detection Algorithm: supporting the above, integrating Airlab’s existing algorithms to ID and locate patients Patient Location Estimation
4. Integration of patient pose algorithm, deploying the current post estimation algorithm developed by Airlab on the Jetson Orin, designed to analyze and extract head and chest orientation. Its performance will be evaluated against active benchmarks on both time and confidence metrics.

PR4 (In Progress)

1. Full Integration of the Path Planning algorithm for Mapping and Searching, in conjunction with Foxglove UI.

2. Patient detection integration for electro-optical camera system in the form of livestream data.

3. Patient re-identification integration for electro-optical camera under naive test algorithm for demonstration.

4. Test of patient pose detection algorithm for lower-level hover.

5. Object and patient segmentation and detection algorithm for FLIR camera.

6. Inter-UAV deconfliction (naive)

7. Mechanical overhaul of system intended for weight reduction and increased stability.

8. FLIR GPS waypoints.