Physical AI-native detection.

One drone-mounted rig fusing cameras, LiDAR and electromagnetic sensing. A model ranks each anomaly and retrains on every item we destroy. Prototype H1 2027.

How it works

Survey

A drone carries cameras, LiDAR and an electromagnetic array over the site in one pass.

Fuse

Onboard AI combines the three sensor streams into one record per anomaly.

Rank

Each anomaly gets a decision: dig, leave or confirm, with location, type and depth.

Hand off

Finds flow into secure destruction on the same custody record.

Drone sensor rig scanning ground, with classified anomalies marked below the surface

Sensor payload

01
Cameras

Colour and thermal, for surface items and disturbed soil.

02
LiDAR

Maps terrain through vegetation, where cameras see only canopy.

03
Electromagnetic

Finds buried metal, including low-metal mines.

One record per anomaly.

In the prototype, sensor streams are fused in flight into one record per anomaly, with location, likely type, depth and a decision. The records go straight to the destruction system.

Learns fromVerified outcomes
OutputRanked dig list
FeedsCustody record
StatusPrototype with design partner, H1 2027
Ranked dig listIllustrative
anomaly     AT blast mine
class       HAZARD
depth_m     0.22
sensors     cam · lidar · em
fused       true
decision    DIG
next        Recover to custody destruction
99%

of excavated items are often non-hazardous when every detected target is dug.

$11.9B

estimated clean-up cost for about 1,700 formerly used US defense sites.

2120

DoD goal for completing munitions response at all remaining sites.

Sources: SERDP-ESTCP, Classification Methods for Military Munitions Response. GAO-22-104744, 2021 DoD estimate. DoD munitions response guidance, Dec 2024.