¶ Harvesting Automation & Robotics
| Company | Forest Grower Research |
| Country | New Zealand |
| Website | https://fgr.nz/research-programmes/harvesting-automation-and-robotics/ |
| Category | Harvesting & Extraction › Remote sensing & mapping |
¶ Overview
Harvesting automation and robotics in forestry refers to the application of autonomous systems, machine learning, advanced sensing, and remote control technologies to reduce or eliminate the need for human operators in the physical tasks of tree felling, processing, and extraction. While conventional mechanised harvesting with harvesters and forwarders already represents a high degree of mechanisation, full automation seeks to remove the operator from the cab entirely — or to substantially augment their capabilities — using technologies such as computer vision, LiDAR-based obstacle detection, GPS/GNSS positioning, and AI-driven path planning. Research institutions and major equipment manufacturers including John Deere, Ponsse, Komatsu Forest, and Caterpillar have invested heavily in prototype autonomous forestry machines, and several field trials have demonstrated machines capable of navigating forest terrain, identifying trees, and initiating felling sequences without direct human input. In Australia, the Forest and Wood Products Australia (FWPA) research body has funded projects examining automation pathways suited to local conditions, including steep terrain harvesting where operator risk is highest and the economic case for remote or autonomous operation is strongest. Tethered remote-control systems — where an operator controls a machine from a safe distance using a joystick and camera feeds — have seen commercial adoption in steep-country operations in New Zealand and Australia as an intermediate step. Robotics research also extends to replanting, thinning, and pruning operations, with robotic pruning arms and seedling-planting machines at various stages of development. Key challenges to full autonomy in forestry include the unstructured nature of the operating environment, variable terrain, the high cost of sensor payloads, and the need for reliable communication infrastructure in remote locations. Australia's relatively large plantation estate, aging harvest workforce, and high labour costs create a compelling environment for continued investment in harvesting automation.
¶ Assessment
A promising system that could improve efficiency and lower labour-related bottlenecks, though its benefits remain mostly conceptual without strong empirical evidence of large-scale productivity or risk-reduction gains.
¶ Details
| Field | Value |
|---|---|
| Company | Forest Grower Research |
| Country | New Zealand |
| Type | Company |
| FWPA RD&E | 4.4 |