Artificial Captain

Artificial Captain, developed by MindChip and TalTech, delivers a comprehensive real-time view of maritime surroundings for enhanced situational awareness on both autonomous and manned vessels. By integrating radar, AIS, and camera data, it detects and tracks objects with precision, ensuring safe navigation.

With effortless remote control and plug-and-play autonomy, Artificial Captain transforms any vessel into a smart, self-sufficient powerhouse.

Robust Situational Awareness

Mindchip’s state-of-the-art Artificial Captain leverages advanced algorithms to ensure safe navigation, detecting and avoiding obstacles in real time with precision and reliability.

Autonomous Working Cycle

Operating fully autonomously along a predefined missions, Artificial Captain continuously collects and monitors data, ensuring optimal performance with minimal human intervention. A user-friendly, web-based interface enables effortless remote monitoring and control.

Mission Management

Plan, schedule, and manage missions with an intuitive interface. Customize routes, set precise timings, and scale to meet varying operational needs.

Specifications

mmWave Radar

mmWave radars provide accurate and reliable information about the surroundings of ships, helping to avoid collisions with other vessels, objects, or obstacles. These radars are capable of detecting objects of various sizes, ranging from large ships to small watercraft, and even floating debris and objects on the water surface.

Object detection with X-band and mmWave radar, computer vision

Machine Vision Cameras

In the context of autonomous ships, machine vision plays a crucial role in enabling them to perceive and respond to the surrounding environment. The visual information collected through cameras and sensors is analyzed using deep learning algorithms, allowing for the identification of various objects such as other ships, maritime markers, rocks, or floating devices. This enables the autonomous ship to assess the situation and make the necessary maneuvers to avoid collisions or navigate through complex sections of the maritime route.

Computer vision, object detection

Simulation and Path Finding Algorithm Test Environment

Conducting physical tests at sea is often time-consuming and expensive. To simplify this process and reduce costs, the MindChip team has developed a virtual testing environment for evaluating and optimizing COLREG-based evasion algorithms. Below is an example of this environment.

Path finding algorithms

Downloads