Distributed Reasoning

Edge Autonomy & Real-Time Intelligence

Synapse pushes decision-making to the edge, enabling split-second reactions without constant links to Cortex through containerized reasoning intelligence.
Edge Reasoning Architecture
Edge Reasoning Architecture

Distributed intelligence across Cortex, Neuron, and Synapse layers

System Architecture Layers

Cortex

Cloud / C2

Global mission orchestration and fleet learning with strategic planning and policy management capabilities.

Example Containers:

Mission Planner
Policy Engine
Model Updater
Neuron

Mesh Communications

Multi-transport routing and link health management enabling resilient swarm connectivity.

Example Containers:

Mesh Router
Link Monitor
Synapse

Edge Runtime

Local perception and reasoning containers providing autonomous decision-making at the edge.

Example Containers:

Local Planner
Threat Evaluator
Consensus Voter
Edge Reasoning Flow Process
Local Perception

Camera, LiDAR, and IMU feed MobileNet-V3 + TinyBERT-6 for environmental understanding

Reason & Act

RRT-Connect generates collision-free paths; evasive maneuvers dispatched instantly

Peer Consensus

Trimmed PBFT achieves quorum < 200ms for formation or task changes

Policy Guardrails

Edge decisions checked against Cortex-pushed ROE & geofences

Up-Sync & Learn

Logs and edge triggers streamed back when links restore; Cortex retrains models incrementally

Intelligent Reasoning Containers

Local Planner

Generates motion paths in real time using sensor fusion, powered by advanced pathfinding algorithms for 3D environments.

RRT-Connect
D*-Lite
Hybrid-A*
Threat Evaluator

Assesses dynamic risks using machine learning for rapid classification and threat prioritization.

Bayesian Filters
XGBoost
GNN Classifier
Consensus Voter

Coordinates swarm behavior via consensus protocols, achieving quorum in under 200ms over LoRa networks.

Trimmed PBFT
Raft
Byzantine Consensus
Local Perception

Optimized neural networks for object detection and context awareness, designed for power efficiency under 5W.

MobileNet-V3
TinyBERT-6
EfficientNet-Lite0
AI Algorithms & Methods Overview
Domain / Function Default Algorithm Hot-Swap Alternatives
CORTEX (Cloud / C2)

Global Orchestration
Mission Planner (A* + MILP)
POMDP Planner
Genetic Planner

Model Training
Federated Averaging
FedProx
F3 Aggregation
NEURON (Mesh Comms)

Mesh Routing
OLSRv2
B.A.T.M.A.N V
AODVv2

Link-Quality Estimation
ETX Metric
EWMPR
LQSR

Channel Selection
UCB1 Bandit
Thompson Sampling
ε-Greedy
SYNAPSE (Edge Runtime)

Object Detection
MobileNet-V3
EfficientNet-Lite0
YOLOv5-Nano

Context Understanding
TinyBERT-6
DistilBERT-Tiny
MiniLM-L6

Path Planning
RRT-Connect*
D*-Lite
Hybrid-A*

Threat Evaluation
Bayesian Particle Filter
XGBoost
GNN Classifier

Consensus
Trimmed PBFT
Raft (encrypted)

Key Benefits of Distributed Reasoning

Reduced Latency

Immediate threat response without cloud round-trip delays

Resilience

Swarm continues in RF-denied or spoofed environments

Scalability

Compute load scales horizontally with node count

Data Security

Raw sensor data stays on board; only insights transmit

Design Considerations & Constraints

Edge model footprint vs CPU/NPU & thermal limits optimization

Deterministic fallback (Return-to-Base) on container failure scenarios

Lightweight consensus vs role hierarchy for conflict resolution

Explainable logs for audit and compliance requirements

Differential model updates to conserve bandwidth and reduce latency

All components are containerized and hot-swappable, ensuring Synapse can evolve with edge hardware and mission parameters while maintaining operational integrity.

Transforming Drones into Thinking Agents

Synapse's distributed reasoning architecture enables autonomous drones to act independently with precision, while still collaborating effectively as a swarm. Its modular containers—including Local Planner, Threat Evaluator, Consensus Voter, and Perception engines—are lightweight, mission-configurable, and optimized for real-time decision-making.

Each node processes environmental inputs, makes context-aware choices, and participates in quorum-based coordination, even in degraded or disconnected conditions. This architecture transforms each drone from a remote endpoint into a thinking, adapting agent.