Enable robots to interpret and respond to their surroundings in real time. Our perception models are optimized for edge deployment, delivering high accuracy with low latency.
Equip robotic systems with precise detection capabilities to identify objects, obstacles, and hazards, improving navigation, manipulation, and operational safety.
Integrate data from multiple sensors to create a reliable and unified understanding of the environment, increasing robustness in complex and dynamic conditions.
Track objects and movement in real time to support advanced robotic functions such as path planning, automation, and interaction with people and environments.
Ensure safe and reliable operation of robotic systems in real-world environments. We design AI safety layers that minimize risk, enable compliance, and support human-robot interaction.
Enable robots to interpret and respond to their surroundings in real time. Our perception models are optimized for edge deployment, delivering high accuracy with low latency.
A brief description of a use case where Visage Technologies can help within the robotics industry.
Advanced perception capabilities
Social robots need to perceive and understand the people around them in order to support natural, responsive interactions. Developing reliable face tracking, recognition, and behavioral analysis capabilities internally can require significant computer vision expertise, training data, and development time. The client needed proven perception technology that could be integrated into an existing robotic platform without building the entire computer vision stack from scratch.
Component providing face tracking, emotion analysis, and facial recognition
We delivered a ready-to-integrate perception component providing real-time face tracking, facial recognition, and facial-expression analysis. The system enables the robot to detect and continuously track people, recognize previously enrolled users, and extract visual signals that can be used by higher-level interaction logic. These capabilities allow applications to maintain attention on the person they are interacting with and adapt responses based on available contextual information. The component was designed for integration into an existing robotics architecture, reducing development effort and accelerating deployment of advanced human-robot interaction features.
Robots need to distinguish and respond to individual users
Robots operating in homes, hospitality, healthcare, retail, and other shared environments may interact with many different people throughout the day. Without the ability to distinguish between users, interactions can remain generic and disconnected between sessions. Developers therefore need reliable perception capabilities that allow robotic systems to recognize individuals and maintain the context required for more personalized experiences.
Real-time recognition and user-aware interaction
Face recognition and tracking can provide the identity and presence signals required for personalized robotic interaction. A robot can recognize enrolled users, determine who is currently interacting with it, and pass this information to the application layer where preferences, previous interactions, or user-specific workflows can be retrieved. Continuous tracking helps maintain interaction context even when multiple people are present or moving through the environment. Combined with other AI components such as speech recognition or conversational AI, this creates more natural and personalized experiences while keeping visual perception as a modular component of the overall system.