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Rhoman Aerospace makes any drone multi-purpose with CG-adaptive controls, and provides energy savings of up to 30% with the safest, and most robust drone flight control solutions…

Delivered with a software download

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Technology

Rhoman Aerospace deploys innovative adaptive flight control solutions that are uniquely able to benefit from machine-learning tuning systems applied to embedded tunable parameters and control system gains.
 
Our machine learning adaptive control systems let us 1) get UAV flying faster and at a lower cost than other development options, 2) insert optimizable functions within control-equations and sensor-input-systems to enhance capabilities and obstacle avoidance through ML tuning, and  3) enable UAV self-learning over a shared network for fleet-wide power savings, flight route optimization, and environmental data-share.
 

Enabling Technologies

Essential Capabilities

Machine Learning Adaptive Controls

ML-Adaptive Controls:

  • Self-tune to unique vehicle configurations

  • Uniquely suited for ML tuning w/ prior flight data

  • Integrate enviro-sensor data to multiple levels of the control system

Adaptive CG Algorithms:

  • Auto-account for off-center CG

  • Auto-account for live CG deltas

  • Handle ad hoc payload

ML-Adaptive Controls:

  • Get any unique UAV flying ASAP

  • Enable system optimization

  • Trustworthy obstacle avoidance

Adaptive CG Algorithms:

  • Maintain safety and stability with hanging cargo

  • Deploy payloads to precise drop-zones w/out landing

  • Make any drone multi-purpose

Software Download

Software Download 

Shifting Payload and Orientation.png
PID Tuning.png
Download Autopilot w Mouse.png
Download Autopilot.png
Coding Python B&W.png
No Land Power Savings Burndown.png
Deployed Python.png
Drone to Cargo Delivery Drone.png
All Drone Types Flying.png

Tuning & Optimization

ML-Adaptive Controls:

  • Self-tune to unique vehicle configurations

  • Uniquely suited for ML tuning w/ prior flight data

  • Integrate enviro-sensor data to multiple levels of the control system

Adaptive CG Algorithms:

  • Auto-account for off-center CG

  • Auto-account for live CG deltas

  • Handle ad hoc payload

Power Saving Algorithms:

  • Reduce RPM-differentials

  • Optimally orient vehicle

Control Barrier Functions:

  • Use prior flight data for tuning

  • Create theoretical flight path guarantees

ML-Adaptive Controls:

  • Get any unique UAV flying ASAP

  • Enable system optimization

  • Trustworthy obstacle avoidance

Adaptive CG Algorithms:

  • Maintain safety and stability with hanging cargo

  • Deploy payloads to precise drop-zones w/out landing

  • Make any drone multi-purpose

Power Saving Algorithms:

  • Keep motor in most efficient RPM range

  • Reduce power use

Control Barrier Functions:

  • Create trustworthy flight path routes
    Enable trustworthy obstacle avoidance

Software Download

Software Download 

Tuning Curves.png
Shifting Payload and Orientation.png
PID Tuning.png
Increased Thrust v RPM.png
Download Autopilot w Mouse.png
Download Autopilot.png
Coding Python B&W.png
No Land Power Savings Burndown.png
Deployed Python.png
Drone to Cargo Delivery Drone.png
All Drone Types Flying.png
Sim Enviro Power v Distance Comparison.png
Optimal Motor RPM Graph.png

Fleetwide UAV Capabilities

ML-Adaptive Controls:

  • Self-tune to unique vehicle configurations

  • Uniquely suited for ML tuning w/ prior flight data

  • Integrate enviro-sensor data to multiple levels of the control system

Adaptive CG Algorithms:

  • Auto-account for off-center CG

  • Auto-account for live CG deltas

  • Handle ad hoc payload

Power Saving Algorithms:

  • Reduce RPM-differentials

  • Optimally orient vehicle

Control Barrier Functions:

  • Use prior flight data for tuning

  • Create theoretical flight path guarantees

Flight Navigation Layer:

  • Target layer between waypoints and vehicle navigation that is tunable with out ML systems and prior flight data

Shared Data Systems:

  • Fleet-wide data increases fidelity and ML model robustness

  • Networked UAV paths can be shared with the cloud and UAV

  • Environmental data is saved and sharable to connected UAV

ML-Adaptive Controls:

  • Get any unique UAV flying ASAP

  • Enable system optimization

  • Trustworthy obstacle avoidance

Adaptive CG Algorithms:

  • Maintain safety and stability with hanging cargo

  • Deploy payloads to precise drop-zones w/out landing

  • Make any drone multi-purpose

Power Saving Algorithms:

  • Keep motor in most efficient RPM range

  • Reduce power use

Control Barrier Functions:

  • Create trustworthy flight path routes
    Enable trustworthy obstacle avoidance

Flight Navigation Layer:

  • 100% Precision flight path following

  • Hit waypoints and security perimeters with 100% accuracy

  • Whole fleet gets cumulative benefits

Shared Data Systems:

  • Environmental data share: geo-tagged, network-distributed 3D point clouds and enviro maps

  • Backup shared optical positioning

  • Optimized tuning parameters reach new drones in fleet

  • 2X Safety positioning redundancy

Software Download

Software Download 

Tuning Curves.png
Shifting Payload and Orientation.png
PID Tuning.png
Increased Thrust v RPM.png
Download Autopilot w Mouse.png
Download Autopilot.png
Coding Python B&W.png
3D Point CLoud Map of Area.png
No Land Power Savings Burndown.png
Flight Route Optimization Comparison.png
Deployed Python.png
Drone to Cargo Delivery Drone.png
3D Area Maps with Bayesian Probabailities.png
All Drone Types Flying.png
Sim Enviro Power v Distance Comparison.png
Optimal Motor RPM Graph.png

Building off of our machine learning adaptive controllers, and leveraging the unique advantages of these systems, we provide value-add control systems to individual drones and fleetwide, scalable benefits to complete drone networks and operations.

UniqueX3

The unique combination of X1: ML-adaptive controls, X2: tuning from prior and shared flight data, and X3: macro-system connectivity and data-share allow Rhoman and our partners to create a system that solves immediate drone pain points and delivers essential future solutions.
 

Synthetic GPS

Drone-Drone Interaction & Swarms

Safe & Trustworthy Autonomy

Future AI & 3rd Party Tech

Software Download Solutions

Our machine learning adaptive control systems let us 1) get UAV flying faster and at a lower cost than other development options, 2) insert optimizable functions within control-functions and sensor-input-systems to enhance capabilities and obstacle avoidance through ML tuning, and  3) enable UAV self-learning over a shared network for fleet-wide optimization and data-share.
 

Rhoman ML-Adaptive Control Systems minimize cost functions based on realized flight path versus planned flight path trajectories through a 'flight-path-optimization' layer enabling precise flight routes

Rhoman Controls and Cloud System
Cloud Controls System.png

TYPOGRAPHY

Our machine learning adaptive control systems let us 1) get UAV flying faster and at a lower cost than other development options, 2) insert optimizable functions within control-functions and sensor-input-systems to enhance capabilities and obstacle avoidance through ML tuning, and  3) enable UAV self-learning over a shared network for fleet-wide optimization and data-share.