Toward Autonomous Vehicles and Machinery in Mill Yards of the Forest Industry: Technologies and Proposals for Autonomous Vehicle Operations

The use of autonomous systems on the wood processing sites of forest industries can significantly increase safety, productivity, and efficiency by reducing the number of monotonous and dangerous tasks conducted by human labor utilizing heavy machinery. However, autonomous machines are challenging and difficult to implement in the mill yards environment because of the dynamic and complex working environment, and partly unstructured processes. The inherent complexity of wood handling and storage tasks is requiring significant human expertise. Fast advancements in sensor technologies, machine learning techniques, and increases in the computational power enable progress in automated operation framework and algorithms development. This opens the door to introduce novel autonomous systems into this environment. With the aim of gaining a better understanding of current issues and facilitating optimal strategies for deploying high-level autonomous systems for the mill yard environments, this study: (1) Utilized a systematic literature review to map current autonomous technologies and algorithms suitable for adoption by the forest industry in automation of vehicles working in mill yards; (2) Summarizes and discusses the potential feasibility of the considered sensors and systems, adaption strategy, and high-level autonomous machinery implementation challenges in the mill yard environment; and (3) Proposes a system framework that integrates multiple technologies to enable autonomous navigation and material handling in mill yards. The study is the first of its kind as a comprehensive study on autonomous vehicles and machinery in mill yard environments. Our novel framework aids in the identification of follow-up research areas and thus promotes the adoption and use of complex autonomous systems in industrial environments.