aQuatonomous is a multidisciplinary student engineering design team at Queen’s University focused on building autonomous surface vehicles (ASVs) for international competition. We compete annually at RoboBoat, developing fully autonomous systems capable of perception, navigation, and real-world task execution.
Our software team is at the core of this autonomy — turning sensor data into intelligent decisions that allow the boat to operate fully autonomously in dynamic environments.
As we prepare for the 2026–2027 season, we are hiring Software Executives to lead the development of our full autonomy stack.
💻 Software Team OverviewThe Software Team is responsible for building the complete autonomy stack using ROS2, Python, and C++. This includes perception, mapping, planning, and system integration.
The team works across:
- Simulation
- Mapping & perception
- Computer vision
- Autonomous planning
- Vehicle-level software
Together, these systems allow the boat to understand its environment, make decisions, and execute tasks reliably in competition.
The team structure consists of:
- 1 Director
- Computer Vision Lead
- Simulation Lead
- Navigation & Control Lead
- Mapping Lead
As Director, you will oversee the entire software architecture and ensure all subteams integrate into a cohesive, high-performing autonomy system.
Responsibilities:
- Oversee all software subteams and maintain alignment across the autonomy stack
- Ensure smooth integration between perception, mapping, planning, and controls
- Guide technical decisions and system architecture
- Support planning, coordination, and progress tracking
- Help drive system-level debugging, testing, and deployment
You will lead the development of the vision system that enables the boat to interpret visual data.
Responsibilities:
- Develop computer vision pipelines using cameras and sensor fusion
- Train and deploy models (e.g., YOLO and other ML approaches)
- Build and manage datasets for training and validation
- Optimize performance using tools like CUDA and PyTorch
- Work closely with mapping and planning for perception integration
You will build and maintain the simulation environment that enables fast development and testing.
Responsibilities:
- Develop and maintain simulation environments in Gazebo and Python
- Model sensors (camera, LiDAR, GPS, IMU) and vehicle dynamics
- Ensure all software components run reliably in simulation
- Create testing scenarios for different competition tasks
- Support sim-to-real transfer and validation
You will design the decision-making system that drives autonomous behavior.
Responsibilities:
- Develop decision logic (state machines, behavior trees, etc.)
- Build the planning stack to convert perception into actions
- Design vehicle motion strategies and trajectory planning
- Ensure smooth and efficient navigation through tasks
- Integrate with computer vision and mapping for full autonomy
You will lead the system that builds and understands the boat’s environment using LiDAR.
Responsibilities:
- Process LiDAR data for environment understanding
- Implement clustering, object detection, and classification
- Develop obstacle avoidance systems
- Build mapping pipelines for navigation and planning
- Work closely with perception and planning teams
This is your chance to:
- Work on real-world robotics and autonomy systems
- Build a full end-to-end autonomy stack
- Gain experience with ROS2, simulation, AI/ML, and planning systems
- Solve complex, real-world problems in dynamic environments
Application Deadline: April 25th, 2026
Term: May 2026 – May 2027
Time Commitment: ~10–15 hours/week (increases during testing & competition)
For questions about the position or application process, please contact:
Email: aquatonomous @engsoc.queensu.ca
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