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One Chip.
Complete Autonomy.

Multi-modal sensor fusion, AI inference, and real-time control—all in a single SoC. Built for drones, robots, and autonomous fleets.

Challenges in Autonomous Vehicle Development

The development of autonomous vehicles is primarily challenged by fragmented architectures that increase system latency and complexity. Meeting real-time processing demands for multi-modal sensor data creates significant computational bottlenecks, while the high power consumption of these systems imposes severe thermal and energy constraints on vehicle performance.

Unified Edge AI Architecture

SteadyBeat’s Autonomous Vehicles AI Module integrates multi-modal sensor processing, AI inference, and vehicle control into a single, power-efficient SoC designed specifically for autonomous vehicle applications.

Advanced ANC

Real-time analysis and adaptive noise cancellation algorithms

Multi-Modal Fusion

Acoustic, visual, physiological, and environmental sensors

Edge AI Processing

On-chip inference with <10ms latency, privacy-preserving

How It Works

1

Multi-Modal Sensor Fusion

Integrated processing of camera, LiDAR, radar, acoustic, and environmental sensors provides comprehensive situational awareness with redundant perception for safety-critical applications.
2

Edge AI Inference

Hardware-accelerated neural network processing enables real-time object detection, classification, tracking, and behavior prediction with sub-10ms latency.
3

Intelligent Decision Making

Advanced algorithms synthesize multi-modal perception data to make safe, efficient navigation decisions—path planning, obstacle avoidance, and behavior prediction.
4

Vehicle Control Integration

Direct control interfaces (CAN, Ethernet) enable seamless integration with vehicle actuators, eliminating the need for separate control units and reducing system latency.

Key Benefits

Unified AI Inference & Control

Integrated Edge AI SoC combines multi-modal sensor fusion, AI inference, and vehicle control in a single chip, eliminating the need for multiple processing units and simplifying system architecture.

Technical Achievement

Single-chip solution with integrated NPU, DSP, and control interfaces

Ultra-Low Power Consumption

Optimized edge computing architecture achieves high-performance AI processing while consuming less than 10W, extending vehicle range and reducing thermal management requirements.

Technical Achievement

Advanced power management with dynamic voltage/frequency scaling

Real-Time Decision Making

Sub-10ms latency from sensor input to control output ensures safety-critical decisions are made instantly, even in complex urban environments.

Technical Achievement

Hardware-accelerated AI inference with deterministic real-time OS

Production-Ready Modularity

Flexible, modular design supports various autonomous vehicle platforms—from delivery robots to passenger vehicles—accelerating time-to-market and reducing development costs.

Technical Achievement

Standardized interfaces with scalable processing capabilities

Real-World Applications

See how our unified AI module powers different autonomous vehicle platforms

Autonomous Delivery Robots

Situation

Last-mile delivery robots navigate crowded sidewalks and crosswalks, requiring real-time obstacle detection, path planning, and decision-making in unpredictable urban environments.

Solution

  • Unified AI module processes camera, LiDAR, and acoustic data in real-time
  • Instant navigation decisions with multi-modal obstacle detection
  • Minimal power consumption extends operational hours per charge

Outcome

Extended operational hours per charge, safer navigation in complex environments, and reduced system cost through integrated architecture.

Autonomous Shuttles

Situation

Low-speed autonomous shuttles in campuses, airports, and business parks require reliable perception and decision-making while maintaining passenger comfort and safety.

Solution

  • Multi-modal sensor fusion combines visual, acoustic, and environmental data
  • Edge AI processing ensures real-time response for comprehensive situational awareness
  • Redundant perception systems enhance safety and passenger trust

Outcome

Enhanced safety through redundant perception, smooth ride quality, and predictable behavior that builds passenger trust.

Agricultural Autonomous Vehicles

Situation

Autonomous tractors and harvesters operate in challenging outdoor environments with varying lighting, weather, and terrain conditions.

Solution

  • Robust multi-modal AI processing adapts to diverse environmental conditions
  • Acoustic sensing detects mechanical issues and environmental hazards proactively
  • All-weather operation with adaptive algorithms for varying lighting and terrain

Outcome

Reliable operation in all conditions, proactive maintenance through acoustic monitoring, and improved operational efficiency.

Ready to Accelerate Your Autonomous Vehicle Development?

Discover how SteadyBeat’s unified AI module can simplify your system architecture and accelerate time-to-market.

Get StartedContact Our Team