ROZOR technology platform
A unified autonomy foundation engineered through real-world deployment.
ROZOR’s technology platform brings together sensing, AI vision, navigation, hardware architecture, and secure data systems into a single, scalable autonomy foundation for indoor robots and autonomous vehicles.
Modular autonomy layers powering adaptable robotic systems.
ROZOR’s platform is built as a layered autonomy stack, where sensing, intelligence, and system infrastructure are developed as modular yet interoperable components.
This design allows the same core platform to adapt across different robotic form factors, environments, and operational requirements, without redesigning the entire system.
Sensing & Perception
Multi-modal sensing combining cameras, LiDAR, radar, and inertial data to build a reliable understanding of the environment.
AI Vision & Decision Intelligence
Onboard AI models process sensor data for perception, object understanding, and real-time decision-making.
Navigation & Control
Localization, mapping, and path planning systems guide safe, efficient motion across structured and unstructured indoor environments.
Hardware & System Architecture
Integrated compute, power, and actuation infrastructure designed for real-time autonomy and long-duration operation.
Core autonomy layers of our platform.
AI Vision & Perception
The AI Vision layer enables autonomous systems to perceive, understand, and track indoor environments in real time, transforming raw sensor inputs into a stable and actionable representation of the world.
By combining data from cameras, LiDAR, radar, depth sensors, and inertial measurements, the system maintains reliable perception even under noise, occlusion, or changing conditions.
This layer provides spatial awareness that feeds navigation, interaction, and downstream autonomy modules, ensuring dependable situational awareness in GPS-denied indoor environments.
Sensor Modalities
Camera, LiDAR, radar, depth, and inertial sensing fused in real time.
Closed-Loop Autonomy
Continuous feedback between sensing, decision-making, and execution.
Research-driven autonomy, validated in real-world environments.
Field Testing & Deployment
Systems are evaluated in real indoor environments to assess behavior under real-world constraints such as noise, dynamics, and environmental variability.
Data-Driven Iteration
Measured performance data feeds back into system design, driving continuous refinement across perception, navigation, and infrastructure layers.
Prototyping & Lab Validation
Validated concepts are implemented on real hardware and tested in controlled laboratory environments to measure performance, robustness, and system limits.
Simulation & Modeling
System behavior and autonomy logic are first developed and tested in simulation, enabling rapid experimentation and early validation before hardware deployment.
