Autonomy Division
Unveiling the Stack
AI-powered systems for object detection, lane recognition, and real-time decision-making.
Learn MoreOur Ambition
To become the leader in autonomous vehicle perception, enabling safer, smarter, and more accessible transportation solutions.
Core Capabilities
Perception Engineering
Object Detection
We are developing AI models aimed at detecting vehicles, pedestrians, and obstacles across varying conditions. Early prototypes are being tested in controlled environments.
Lane Recognition
Our team is exploring computer vision and deep learning approaches for lane detection and tracking. Initial research is focused on highway and urban road scenarios.
Real-time Decision Making
We are investigating edge computing architectures to reduce latency in driving decisions. Current benchmarks are being evaluated against safety-critical thresholds.
Safety Systems
We are researching redundant safety mechanisms to ensure fail-safe behavior in edge cases. Simulation testing is a key part of our current validation process.
Neural Architecture
We are designing and iterating on custom neural network architectures tailored to autonomous driving perception. Model training and validation are ongoing.
Sensor Integration
Research is underway to fuse data from LiDAR, radar, and camera inputs into a unified perception layer. We are prototyping multi-sensor calibration frameworks.
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