FORWARD: Dataset of a forwarder operating in rough terrain
Mikael Lundb\"ack, Erik Wallin, Carola H\"aggstr\"om, Mattias Nystr\"om, Andreas Gr\"onlund, Mats Richardson, Petrus J\"onsson, William Arnvik, Lucas Hedstr\"om, Arvid F\"alldin, Martin Servin

TL;DR
FORWARD is a comprehensive multimodal dataset capturing the operation of a forest forwarder in rough terrain, aimed at advancing AI models for autonomous forestry machinery and terrain interaction analysis.
Contribution
This paper introduces FORWARD, a detailed, multimodal dataset with synchronized sensor data, video, and terrain information for forest machine operation in challenging environments.
Findings
Dataset includes 18 hours of real-world forestry operations.
Annotations of work elements and scenario specifications are provided.
Data supports development of AI for terrain assessment and autonomous control.
Abstract
We present FORWARD, a high-resolution multimodal dataset of a cut-to-length forwarder operating in rough terrain on two harvest sites in the middle part of Sweden. The forwarder is a large Komatsu model equipped with vehicle telematics sensors, including global positioning via satellite navigation, movement sensors, accelerometers, and engine sensors. The forwarder was additionally equipped with cameras, operator vibration sensors, and multiple IMUs. The data includes event time logs recorded at 5 Hz of driving speed, fuel consumption, machine position with centimeter accuracy, and crane use while the forwarder operates in forest areas, aerially laser-scanned with a resolution of around 1500 points per square meter. Production log files (Stanford standard) with time-stamped machine events, extensive video material, and terrain data in various formats are included as well. About 18 hours…
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Taxonomy
TopicsForest Biomass Utilization and Management · Forest Management and Policy · Agriculture and Farm Safety
