Treetle
A speculative human–machine system for low-impact forest thinning.
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problem
Forest precommercial thinning relies heavily on skilled operators working within complex, sensitive ecosystems. As skilled labour becomes increasingly scarce, early-stage thinning decisions are more prone to human error. Errors that can negatively impact forest health and biodiversity for decades. Existing machinery prioritizes efficiency over ecological nuance, offering limited support for site-specific, low-impact decision-making.
solution
Treetle is a compact, semi-autonomous thinning system designed to support sustainable, site-specific forest management. By combining autonomous navigation, ecological decision parameters, and human oversight, Treetle reduces operator workload and error while enabling selective, low-impact thinning that prioritizes long-term forest health and biodiversity.
Treetle emerged from the Hot Teams Studio at Umeå Institute of Design, a course centered on collaborative design, ambiguity, and systems thinking. The project challenged teams to engage with real world forestry contexts and explore how design might mediate interactions between humans, machines, and nature. The outcome reflects both a speculative design proposal and a learning process rooted in research, iteration, and shared authorship.
year
2025
timeframe
4.5 Weeks
tools
Solidworks, Shapr3D, Photoshop
category
Human-Machine Systems Design
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see also
