Micro Autonomy Quest Book - Winter 2025
The Great Objective: Fully Autonomous F1tenth Racing Car with LiDAR and Camera
Micro Autonomy aims to win the F1teneth Autonomous Racing Competition in the future
Term Objectives Summary
The objectives for this term focuses on setting up hardware and developing the autonomy software stack. This includes:
-
Hardware Setup
- Setup everything including Jetson, LiDAR and VESC to work properly and publish ros messages needed for autonomous navigation
-
State Estimation
- Estimates current position of vehicle relative to last position using Kalman Filter
-
Mapping: SLAM
- Generate a map in image format and a yaml file for the map specifications based on IMU, encoder and LiDAR specifications
-
Raceline Generation/Optimization
- Generate a optimized raceline as global trajectory (ideal path) for the race car to follow to minimize lap time
-
Planning: Lattice Planner
- Generate local trajectories for obstacle avoidance and following global trajectory during Racing
-
Controls: Pure Pursuit
- Controls the vehicle's steering and trottle to following the trajectories genereated by the planning module
-
Hardware Setup
| Score | Criteria |
|---|---|
| 10/10 | Setup interfaces for sensors to publish readings and actuators to take ROS topic commands |
| 7/10 | Assemble all components for F1Tenth Car to start autonomous movement |
| 5/10 | Assemble all (within current budget) components |
| 3/10 | Purchase & manufacture all (within current budget) components |
| 0/10 | No Progress |
Minimum Requirements: Assemble all available components (7/10)
- State Estimation
| Score | Criteria |
|---|---|
| 5/5 | Estimates position based on IMU, encoder and LiDAR in actual vehicle |
| 3/5 | Estimates position based on IMU, encoder and LiDAR in simulation |
| 0/5 | No Progress |
**Minimum Requirements:*Estimates position in simulation (3/5)
- Mapping: SLAM
| Score | Criteria |
|---|---|
| 10/10 | Map and yaml file generated through state estimation and LiDAR scans on actual vehicle |
| 8/10 | Map and yaml file generated through state estimation and LiDAR scanes in simulation |
| 5/10 | Map and yaml file generated through true position (odometry) and LiDAR scans in simulation |
| 0/10 | No Progress |
**Minimum Requirements:*Can generate a map and yaml file in simulation (5/10)
- Raceline Generation/Optimization
| Score | Criteria |
|---|---|
| 10/10 | Optimizes centerline to generate a raceline that minimizes actual lap time based on complex vehicle dynamics |
| 7/10 | Optimizes centerline to generate a raceline that minimizes steering or total curvature and generates velocity profile |
| 3/10 | Generates a centerline for testing purposes for the vehicle to follow |
| 0/10 | No Progress |
**Minimum Requirements:**Optimizes centerline to generate a raceline that minimizes steering or total curvature (7/10)
- Planning: Lattice Planner
| Score | Criteria |
|---|---|
| 10/10 | Genenerates/optimizes local trajectory based on cost map and vehicle dynamics to achieve obstalce avoidance on actual vehicle |
| 9/10 | Genenerates/optimizes local trajectory based on cost map and vehicle dynamics to achieve obstalce avoidance |
| 8/10 | Generates local trajectory by using a cost map to achieve obstacle avoidance when obstalces are on the ideal path |
| 5/10 | Generates local trajectory to make vehicle follow the raceline (ideal path) |
| 0/10 | No Progress |
**Minimum Requirements:**Generates local trajectory by using a cost map to achieve obstacle avoidance when obstalces are on the ideal path (7/10)
- Controls: Pure Pursuit
| Score | Criteria |
|---|---|
| 10/10 | Follows local trajectories and ideal velocities smoothly on actual vehicle |
| 8/10 | Follows local trajectory generated by planning through controlling steering angle and throttle based on velocity profile |
| 4/10 | Follows a global trajectory by controlling steerring angle with a constant velocity |
| 0/10 | No Progress |
**Minimum Requirements:**Follows local trajectory generated by planning through controlling steering angle and throttle based on velocity profile (9/10)
- Integration
| Score | Criteria |
|---|---|
| 10/10 | Full software integration & hardware interfaces for real life autonomous racing |
| 8/10 | Full software integration in simulation for autonomous driving, limited hardware interfaces |
| 4/10 | Limited software integration between components |
| 0/10 | No progress |
Minimum Requirements: Full software integration in simulation for autonomous driving (8/10)
Scoring Template
| Quest Name | Description | Due Date | Score |
|---|---|---|---|
| Hardware Setup | Setup everything including Jetson, LiDAR and VESC to work properly and publish ros messages needed for autonomous navigation | 2025-04-31 | 3 |
| State Estimation | Estimates current position of vehicle relative to last position using Kalman Filter. | 2025-04-31 | 3 |
| Mapping: SLAM | Generate a map in image format and a yaml file for the map specifications based on IMU, encoder and LiDAR specifications. | 2025-04-31 | 5 |
| Raceline Generation/Optimization | Generate a optimized raceline as global trajectory (ideal path) for the race car to follow to minimize lap time. | 2025-04-31 | 7 |
| Planning: Lattice Planner | Generate local trajectories for obstacle avoidance and following global trajectory during Racing. | 2025-04-31 | 5 |
| Controls: Pure Pursuit | Controls the vehicle's steering and trottle to following the trajectories genereated by the planning module. | 2025-04-31 | 8 |
| Integration | Full software integration & hardware interfaces for real life autonomous racing | 2025-04-31 | 4 |