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Path planning plays a pivotal role in additive manufacturing by determining the movement of the toolhead during material deposition, which directly affects print quality, material usage, manufacturing efficiency, and functional performance. This review systematically examines recent developments in path planning strategies across various AM processes. We categorize existing approaches based on their primary objectives, including enhancing print quality, reducing time and material consumption, and achieving specific printing properties such as mechanical strength, aesthetics, or thermal/electrical performance. Emerging trends such as energy-aware path planning, multi-objective optimization, and learning-based strategies are also discussed. Finally, we identify current challenges and outline promising research directions, including generalizable planning frameworks, trade-off analysis between objectives, and standardized benchmarking. This review aims to serve as a valuable reference for researchers and practitioners seeking to optimize AM processes through innovative path planning techniques.
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Zhang et al. (2025) studied this question.
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