Autonomous Defence Crawler
Tracked unmanned ground vehicle for reconnaissance and surveillance in rough terrain.
- Domain
- Defence
- Platform
- SSM Autonomy
- Readiness
- To be confirmed
Platforms
SSM Autonomy
The decision-making core for machines that move on their own. SSM Autonomy takes a vehicle from sensor data to a safe, planned action, on the ground, in the air or in orbit.
Capabilities
Autonomous navigation, SLAM, path planning, control, obstacle avoidance and mission intelligence.
- Autonomous navigationGNSS-aware and GNSS-denied navigation for rough terrain and indoor sites.
- SLAMSimultaneous localisation and mapping from LiDAR, cameras and IMU.
- Path planningGlobal routing and local re-planning around live obstacles.
- ControlMotion and actuator control tuned to each vehicle's dynamics.
- Obstacle avoidanceReal-time detection and avoidance from fused sensor data.
- Mission intelligenceTask allocation, waypoints and autonomous decision-making in the field.
Where it's used
Typical deployments. Every system is configured to the vehicle, asset or environment it runs in.
- Defence ground robotsReconnaissance and surveillance crawlers that operate beyond line of sight.
- Agricultural roversField robots that navigate crop rows and work through the season.
- Industrial AGVsMaterial movement on factory floors and in warehouses.
Projects on this platform
Prototypes and systems built on SSM Autonomy.
Autonomous Drone Intelligence
Onboard edge AI for autonomous flight, object detection and inspection missions.
- Domain
- Aerospace
- Platform
- SSM Aerospace AI
- Readiness
- To be confirmed
Other platforms
Most systems combine more than one.
SSMDigital Twin
Real-time asset monitoring, anomaly detection, RUL prediction, simulation and optimisation.
SSMRobotics
UGV, AGV, robotic arms, inspection robots, agricultural robots and physical AI.
SSMAerospace AI
Drone autonomy, star trackers, satellite analytics, orbital collision prediction and space robotics.
SSMQuantum
Quantum optimisation, quantum ML, post-quantum security and hybrid quantum-classical workflows.
Talk to the SSM Autonomy team.
Share your use case and constraints. We'll come back with a technical approach, a demo and a realistic path to deployment.