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Organization: Kodama Systems
Country: U.S.
Website: https://kodama.ai/
Year Founded: 2021
Number of Employees: 1-10
Innovation Class: Application & Market
In 2022, wildfires burned over 7.5 million acres of land in the U.S., according to the National Centers for Environmental Information. It’s a pressing issue, and it will only get worse as the climate becomes hotter and drier.
While there are some robots deployed to fight these deadly wildfires, few are working to prevent them. This is where Kodama Systems comes in.
Historically, forests in the U.S. were less dense than they are today. Overstocked forests have resulted in greater competition for resources among plant life in these areas, making them more vulnerable to drought and other stressors.
Scientific consensus also suggests that these overgrown forests are a key contributor to the current wildfire crisis. An abundance of smaller, often weaker, trees is ready to burn.
To combat this overgrowth, government agencies have been increasingly investing in initiatives aimed at thinning out these forests. This is a labor-intensive task, as it requires a number of heavy machines to drive into the forest, cut down the trees, and then haul them out so they can be cut to size and delivered to sawmills to be processed.
Sonora, Calif.-based Kodama Systems is working to add autonomy to the process. It creates teleoperation and autonomy kits for the heavy machinery at work. The team started with the skidder, a piece of equipment used to haul cut-down trees out of the forest.
“Our mission is to restore forests for future generations, help promote forest health for the long term, and accelerate the work that the state and federal agencies are calling for right now,” James Sedlak, co-lead for operations and communications at Kodama, told The Robot Report.
In 2023, the company deployed its teleoperation platform on a small forest-thinning project in the Stanislaus National Forest. During this project, the company’s skidder autonomously dragged bundles of trees along skid trails to the project landing.
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