Finding
Forestry machines automate the crane before the drive, because the forest floor is too uneven and varied for driverless travel
The cut-to-length harvesters and forwarders built by Ponsse in Finland, Komatsu Forest in Sweden and John Deere in Finland now move their booms under computer control: John Deere's Intelligent Boom Control and comparable Ponsse and Komatsu systems let the operator point the head while software coordinates the joints. Driving between trees on soft, rocky, sloped ground is still done by a person.
Autonomous forwarders, which carry cut logs to the roadside over a route the harvester has already opened, are the next step and are being tested in Nordic research programs. On slopes too steep for wheels alone, tethered winch-assist machines from makers such as Ecoforst and HAAS let harvesters work in the Pacific Northwest and New Zealand with the operator still on board.
Drones handle the rest. DJI and other makers' lidar drones map stands and count trees, Mast Reforestation (formerly DroneSeed) replants burned areas by drone, and Rain is building autonomy for firefighting helicopters with Sikorsky. Electrification is early: battery-electric and hybrid forwarder prototypes exist, but full-size machines work days from grid power. See Electric Forestry Equipment.
Operators
Leading forestry autonomy players
Status is an ElectronsX summary.
| Company | Machines | Powertrain | Status |
|---|---|---|---|
| Ponsse | Harvesters and forwarders with crane automation; EV1 electric forwarder concept | Diesel; electric concept | Operator assist commercial |
| Komatsu Forest | Harvesters and forwarders with Smart Crane | Diesel | Operator assist commercial |
| John Deere | Intelligent Boom Control on harvesters and forwarders | Diesel | Commercial |
| Tigercat | Steep-slope harvesters and feller bunchers | Diesel | Remote-control and assist features |
| Ecoforst and HAAS | Winch-assist tether machines | Diesel | Commercial on steep slopes |
| DJI | Mapping and patrol drones | Battery-electric | Commercial worldwide |
| Mast Reforestation | Seed-dispersal drones | Battery-electric | Early commercial in the western US |
| Rain | Autonomy for firefighting aircraft, with Sikorsky | Aircraft fuel | Development and trials |
Segments
Forestry autonomy by task
| Segment | Size | Readiness | Constraint |
|---|---|---|---|
| Harvesters | 20-40 ton, wheeled or tracked | Boom automation commercial; driving manual | Terrain, machine cost |
| Forwarders | 15-25 ton | Research and trials | Navigation off trail, remote connectivity |
| Forestry drones | Mapping and patrol | Commercial | Flight rules, battery endurance |
| Robotic planters | Seed drones, ground planters | Early commercial | Seedling survival rates |
| Steep-slope systems | Winch-assist tethers, yarders | Commercial with operator | Niche, high setup cost |
Stack
Forestry fleet stack
| Layer | Typical hardware or software | Role |
|---|---|---|
| Sensors | Lidar, stereo cameras, GNSS with RTK, IMUs | Tree detection, terrain mapping, machine stability |
| Crane control | Boom-tip control software | Coordinate joints so the operator steers only the head |
| Compute | OEM embedded controllers, NVIDIA Jetson Orin | Perception and operator assist |
| Connectivity | Private LTE where available, satellite backhaul | Remote monitoring, data from harvest files |
| Planning | Harvest plans, stand maps from drone lidar | Choose trees and routes before machines arrive |
Sources
Sources and scope
- Scope
- Autonomous Forestry Fleets
- Sources
- Ponsse, Komatsu Forest, John Deere, Tigercat, Mast Reforestation, Rain and DJI company materials; ElectronsX analysis
- Updated
- October 2026