AI onboard
Sensor fusion, pattern recognition, event detection and prioritization directly on the robot.
Technology
Technology
A full robotics stack, from actuator to autonomous fleet.
MARSBOTS combines vehicle dynamics, artificial intelligence, multi-sensor fusion and predictive analytics. We are developing autonomous robotic systems that process camera, lidar, radar and drilling data onboard and prioritize decision-relevant information.
Sense
Fuse
Assess
Decide
Build
How it works
Terrain Intelligence Engine
From raw sensor data on the surface to prioritized information: the MARSBOTS architecture processes camera, lidar, radar and drilling data directly onboard, understands events on site and delivers only decision-relevant information to Earth.
Terrain analysis, path planning, hazard assessment and anomaly detection form the analytical core.
AI + Physics
AI decides on the robot. Physics anchors the results.
Sensor data is fused, evaluated and prioritized directly onboard instead of being sent to Earth in full. Vehicle dynamics, physical constraints and deterministic models anchor these onboard results and keep them verifiable on ground.
Physics
Vehicle dynamics, terrain models, deterministic calculations and physical constraints.
Validation
Confidence scoring per event, explainable risk, cross-checking on ground and human approval.
Intelligent analysis
Turning observations into predictive intelligence.
Three analytical layers work together: data fusion creates a reliable terrain picture, pattern recognition identifies relevant changes, and predictive analytics evaluates possible developments within physical constraints.
Analysis active
Data fusion
Pattern analysis
Route forecast
Pattern recognition
Machine learning examines terrain imagery, sensor signatures and drive history to identify recurring hazards, subtle slope changes and unusual events that would be difficult to isolate manually.
Terrain · hazard · classification
Data fusion
Radar, camera, lidar and telemetry observations are aligned in time, normalized and cross-checked. The result is one coherent terrain picture with source provenance and visible uncertainty.
Normalize · correlate · validate
Predictive analytics
Physics-constrained models project drive paths, compare candidate routes and update hazard corridors when new observations arrive. Operators see how a route may develop, not only where the robot is now.
Project · compare · anticipate
Independent sensor observations
Cross-source correlation
Robot behaviour over time
Physics-constrained forecast
On-Board AI
Intelligence where the data is generated.
MARSBOTS is being developed as an autonomous system that processes camera, lidar, radar and other sensor data directly onboard robots on the Mars surface. The AI is intended to fuse observations, detect relevant events and prioritize the information that matters most for decisions.
System concept · in development
Autonomous on-board intelligence active
Sensors
On-board AI
Event
Robot fleet
Transmission
Designed for existing mission operations.
Planned interfaces include REST API, real-time alerts, webhooks and data feeds for mission-control and fleet-operations systems. This integration capability is in development.
Talk to our team about integrationREST API
Real-time alerts
Webhooks
Data feeds
Mission-control software
Fleet tracking systems