Auto Dock AI provides AI-powered docking assistance for boaters, using computer vision and sensor data to simplify and improve docking maneuvers. The system offers real-time guidance and automated thruster control, reducing the stress associated with docking in tight spaces and challenging conditions. Its technology is designed to support both experienced captains and those new to boat handling.
Funding
Funding not disclosed
Founders
Product
Problem
Docking a boat remains a complex and stressful maneuver, requiring precise control, spatial awareness, and experience to execute safely in tight marinas, adverse weather, and strong currents. This difficulty can deter new boaters and lead to costly damage, accidents, and anxiety for even seasoned captains.
Solution
Auto Dock AI delivers an automated docking assistance system that uses a suite of sensors, including cameras and lidar, combined with AI-driven perception to detect and track nearby obstacles. The system provides real-time visual and audible guidance to the captain, and can optionally take direct control of the engines and thrusters to execute a precise docking sequence. By integrating with the vessel's existing control systems, Auto Dock AI simplifies the docking process, making it safer, easier, and more accessible to boaters of all skill levels.
Target Audience
Primary customers are recreational boat owners, yacht captains, and marine original equipment manufacturers seeking to enhance vessel safety and ease of operation.
Features
- Multi-sensor fusion combining camera and lidar data for robust 360-degree obstacle detection and environmental mapping in various lighting and weather conditions.
- AI-powered docking algorithm that calculates optimal thruster and propulsion commands for hands-free docking maneuvers.
- Real-time graphical user interface and audio alerts that guide the captain through every step of the docking process.
- Seamless integration with a boat's existing joystick and engine control systems for automated or assisted operation.
- Machine learning models trained on a large dataset of docking scenarios to improve performance in tight spaces, strong winds, and currents.