Labelvisor

The modern stage of autonomous systems development requires a radical overhaul of the principles of interaction between human and machine. In such critically important areas as high-tech manufacturing, robotic medicine, busy logistical ware...

Agent-based robots require an understanding of context, environmental dynamics, risks, and emerging opportunities. Development depends on high-quality annotation pipelines that capture semantic information about the world and transform raw sensor data into structured knowledge.

Current robotics research relies on developing situational awareness datasets, environmental ...

The development of industrial automation and the introduction of Industry 4.0 and Industry 5.0 concepts are significantly changing approaches to human interaction with robotic systems in production. Traditional methods of controlling industrial robots, based on rigidly defined interfaces or programming in specialized languages, often limit the flexibility of production proces...

Traditional autonomous platforms perceive the surrounding space purely as a set of faceless geometric obstacles, where each wall, box, or human figure is merely a set of coordinates to be bypassed. However, the integration of the Model context protocol (MCP) fundamentally changes this approach, allowing the physical perception of the machine to be linked with deep semantic kn...

Many real-world incidents occur even when all system components are functioning as intended. The problem lies in the system’s limitations in perceiving or responding correctly to complex environmental conditions.

To address these, the automotive industry introduced ISO 21448, known as safety of intended functionality (SOTIF). SOTIF addresses the risks arising from funct...