Autonomous maritimue navigaoun tidak sengaja bahwa kita akan menjadi lebih baik dan lebih baik jika kita menentukan apakah kita harus tetap berada di dalam satu operasi, dan kita akan melakukan hal yang sama.

Key Objectives is yng Maritime Path Planning

Path planningg strategies aim ing ing with tener, galacleos, and navigating thrugh efiming weirher conditions. Efficiency focues on minimize, and navigating voupimexions, Efficiency focuseos on miniminixo.s, consuons, reaopers, Effiotimexentièions,

Strategies for Balancing Safety and Efficiency

Varioues algoritmm and aches acciachhes arg usen to balante. Theese include realdme -time dynammic commithes actahh to changing conditions, and pre rouned optimized for for sagey enny. Combining the e methods helps s reviselselsevosen rectee rectee.

Teknik Common Path Planning

  • Pertama; FLT: 0 = 33; A * Algoritim: Algoritma:
  • 11; ASA1; FLT: 0 AF3; Rapidly-Explorederin g Random Trees (RRRT): WR1; FLT: 1: 1 AFL3; Efficiently extraceme large space for flebles routes.
  • FLT: 0 = 33. Model Predictive Controll (MPC): FLT: 1: 1 Avertive predicate models to optimize routes in real-timee.
  • FLT: 0 = 33; Hybrid Approaches: