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AV Engineering Lab

Autonomous vehicle perception stack engineering

Audited ROS2 camera pipelines, sub-millisecond camera-LiDAR calibration, and hardware-agnostic bottleneck profiling for production vehicle fleets.

Telemetry & Profiling

Deterministic perception pipeline benchmarks

< 1.2 ms

camera-LiDAR point cloud fusion delay

0.001%

frame-drop rate across 8x 4K camera streams

100%

hardware-decoupled open-source ROS2 architecture

Cars drive around a street corner at night
Cars drive around a street corner at night
Core Stack Competencies

Hardware-decoupled visual perception modules

ROS2 Integration

Open-source ROS2 vision pipeline

Custom zero-copy CUDA nodes and deterministic transport profiling eliminate kernel bottlenecks across high-bandwidth multi-camera autonomous vehicle arrays.

Sensor Calibration

Sub-millisecond camera-LiDAR calibration

Extrinsic and intrinsic targetless calibration routines maintain sub-millisecond spatial alignment across operating temperature swings and structural vibration.

Adverse weather reliability

Zero phantom braking events

Conventional autonomous vision models trigger catastrophic phantom braking when faced with direct solar glare or airborne precipitation. Vektra isolates camera saturation artifacts before feeding spatial tensors to the path planner.

Executing natively on automotive-grade SoC platforms, our deterministic processing pipeline achieves ISO 26262 functional safety compliance while maintaining real-time object classification across extreme thermal operational windows.

Schedule Stack Audit

Audit your perception pipeline latency

Direct engagement with our Systems Engineering Lab. We profile, harden, and benchmark your open-source perception architecture on target hardware.