F26 Eve Quests

Eve Quest Book - Fall 2026 (F26)

The Great Objective: Level 5 Robo-taxi Around Campus

WATonomous aims to achieve a fully autonomous Level 5 robo-taxi capable of navigating the University of Waterloo campus by the end of Fall 2026. This involves integrating hardware, software, and cognition systems to enable decision-making directly within the car. Achieving this milestone establishes the groundwork for advanced autonomous vehicle research and real-world applications.

Term Objectives Summary

The objectives for Fall 2026 focus on developing lane detection using the existing BEVFusion implementation for perception, developing refined vehicel dynamics for action, simulation in the loop, lots of testing around ring road, and preparing the platform for autonomous operation.

  1. Hardware Integration

    • Hardware Quality of Life
  2. Software Modules

    • BEVFusion
    • Prediction
    • HD Map
    • Localization
    • Local Planner (builds a collision-aware spline)
    • Simulation
    • Controller (MPPI, MPC)

Term Objectives and Scoring

Hardware Integration

  1. Hardware Quality of Life
ScoreCriteria
10/10No more hardware issues with clean cable management, a tidy car, and documentation.
4/10Add additional E-stop to center dashboard.
3/10E-stop no longer engages parking brake when in normal drive mode.
0/10No e-stop improvement.

Minimum Requirements: Add additional E-stop to center dashboard 4/10.

Software Modules (All must be on the main branch)

  1. BEVFusion with Lane lines
ScoreCriteria
10/10Fine-tuning BEVFusion with our own dataset from Wato-World annotations.
5/10Basic BEVFusion setup with lane line segmentation.
0/10No BEVFusion lane line head implementation.

Minimum Requirements: Basic BEVFusion setup with lane line segmentation.

  1. Prediction
ScoreCriteria
10/10Fully tested prediction on the test track.
7/10Fix up and integrate prediction with BEVFusion.
0/10No prediction improvements.

Minimum Requirements: Fix up and integrate prediction with BEVFusion 7/10.

  1. HD Map
ScoreCriteria
10/10Construct a valid HD map plus traffic lights, stop signs, and other regulatory elements from recorded sensor data while driving the car.
7/10Fully tested HD map constructed by driving the car around.
4/10Construct a valid HD map with only lanes and lane boundaries from recorded sensor data while driving the car.
1/10Basic ring road HD map loading and visualization (manually drawn).

Minimum Requirements: Construct a valid HD map with only lanes and lane boundaries from recorded sensor data while driving the car. 4/10.

  1. Localization
ScoreCriteria
10/10Reliable Multi-sensor localization on ring road.
4/10Multi-sensor localization functional on ring road.
0/10Basic localization without GPS on the test track.

Minimum Requirements: Multi-sensor localization functional on ring road for a score of 4/10.

  1. Local Planner
ScoreCriteria
10/10Full HD-map aware elastic trajectory planner tested on the test track.
4/10Basic (naive) elastic trajectory planner tested on the test track.
0/10No local planner improvements.

Minimum Requirements: Basic (naive) elastic trajectory planner tested on the test track for a score of 4/10.

  1. Simulation
ScoreCriteria
10/10Full vehicle tested in simulation (SIL) with less than 5% sim2real control discrepency.
4/10Tested controller in simulation and improved vehicle dynamics (sim2real).
0/10No simulation improvements.

Minimum Requirements: Tested controller in simulation and improved vehicle dynamics (sim2real) for a score of 4/10.

  1. Controller
ScoreCriteria
10/10Full controller tested on test track with improved vehicle dynamics.
4/10Improvements of Adaptive Pure Pursuit.
0/10No controller improvements.

Minimum Requirements: Basic controller for a score of 4/10.


Scoring Template

Hardware Integration

Quest NameDescriptionScore
Hardware Quality of LifeNo more hardware issues with clean cable management, a tidy car, and documentation

Software Modules

Quest NameDescriptionScore
BEVFusionBEVFusion with Lane lines.
PredictionFully tested prediction on the test track
HD MapLoad custom HD maps with regulatory elements
LocalizationMulti-sensor localization with cm accuracy
Local PlannerDynamic obstacle avoidance and smooth navigation
SimulationSIL integration and sim2real development
ControllerAdaptive Pure Pursuit and improved vehicle dynamics