<p>The computer-assisted automatic planning (CAAP) technology for percutaneous liver tumor ablation plays a crucial role in enhancing the precision and safety of minimally invasive treatments. CAAP reduces the manual workload of clinicians through path planning and treatment parameter optimization, while simultaneously improving planning efficiency and clinical reliability. This paper first reviews the basic principles of thermal ablation, including path planning, treatment parameter optimization, and temperature field modeling, and outlines the theoretical foundations of CAAP’s key technologies. The existing methods are then classified according to their technical characteristics, covering traditional optimization algorithms, intelligent optimization methods, and deep reinforcement learning techniques. The focus is on single-needle and multi-needle path planning, multi-objective optimization, and dynamic environmental adaptability technologies. Furthermore, the performance of these methods in automation, real-time processing, and multi-physics modeling is evaluated. Finally, potential future developments are proposed.</p>