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With continued development of forest machines the operators risk becoming a bottleneck, due to the ever increasing pace theyhave to work in. Different kind of aids for the operators will become necessary to lessen the workload. Development of autonomous forest machines aims at meeting this demand. This book describes an ongoing project of which the purpose is designing and developing techniques and algorithms for such a vehicle. The focus is on some of the components necessary to accomplish autonomous navigation, which involves sensing and moving safely along a user-defined path in a dynamic forest environment. A new path-tracking algorithm isintroduced and demonstrated as superior to standard algorithms, such as Follow the Carrot and Pure Pursuit. Localization is accomplished by a neural network that fuses data from a GPS, agyro, and wheel odometry. Results from successful field tests on a full-size forest machine with autonomous path tracking, including obstacle avoidance, are presented. The book will be of interest to students and researchers in the area of autonomous vehicles and artificial intelligence.
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