ENGS 89/90 Reports
Year of Graduation
2023
Sponsor
Kodama Systems
Project Advisor
Fridon Shubitidze
Instructor
Solomon Diamond
Document Type
Report
Publication Date
2023
Abstract
Past forest fire suppression efforts have aimed to prevent all forest fires, which has left forests overstocked with trees and undergrowth and made them less resilient to naturally occurring fires. Kodama Systems is stepping in to address this problem and sequester carbon in a more efficient way. The Thayer team was asked to develop a way to sense the position of one of Kodama’s forestry machines with enough information such that a remote operator could successfully grasp and retrieve a log bundle. The team created three deliverables as a solution for the first part of the grapple arm to advance the sponsor toward this goal: a kinematic model to mathematically define the arm, methods for calibrating sensors, and selection of high quality sensors for use in the design. The team also developed recommendations for the implementation of this system and for the sensing of joints further along the grapple arm. Over the course of the project, the team learned a significant amount about forestry, robotics, and remote sensing. The team hopes that this project will be a meaningful contribution to forest conservation efforts.
Dartmouth Digital Commons Citation
Eubanks, Jesse; Hickey, Taylor; Padilla, Adrian; and Sankey, Logan, "Autonomous forestry to capture carbon and reduce forest fire risk" (2023). ENGS 89/90 Reports. 116.
https://digitalcommons.dartmouth.edu/engs89_90/116
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Available to Dartmouth community via local IP address.
