Edge Encoder→Cloud Decoder→Autonomous Systems
// INDUSTRIES / AUTONOMOUS SYSTEMS

One Feature Stream.
Perception, Planning, Control.

Autonomous vehicles, drones, and robots run multiple vision models simultaneously. Each usually receives a full video stream, multiplying bandwidth demand. Our research explores compressing features once and sharing the same representation across perception, planning, and control — eliminating redundant video transmission.

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The Redundancy Problem
Today
perception → video stream
planning → duplicate video stream
control → another video stream
3× bandwidth. Same pixels. Different consumers.
MAHAMAIA
perception ← features
planning ← same features
control ← same features
1× bandwidth. One feature stream. All consumers.
Multi-model inference from a single compressed feature stream is active research. Currently validated for single-detection pipelines on ResNet50-FPN P4 features.

Day in the Life

Camera captures scene
A drone or robot camera captures the environment. Feature extraction begins at the edge.
MAHAMAIA compresses features
The learned compressor reduces the frame to a compact latent on the onboard Jetson.
One stream, all models
The same compressed feature stream feeds perception (detection), planning (path), and control (actuation).
Coordinated decision
All models execute simultaneously from one representation. No redundant video streams. No duplicate bandwidth.
One feature stream. All consumers.

Multi-model inference from compressed features is active research. Contact us for collaboration or pilot discussion.

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