Motion Pattern Optimization and Energy Analysis for Underwater Glider Based on the Multi-Objective Artificial Bee Colony Method

Underwater gliders are prevailing in oceanic observation nowadays for their flexible deployment and low cost. However, the limited onboard energy constrains application, hence motion pattern optimization analysis key to maximizing range of glider while maintaining acceptable navigation preciseness glider. In this work, a Multi-Objective Artificial Bee Colony (MOABC) algorithm is used solve constrained hybrid non-convex multi-objective problem about accuracy combination with specific dynamics models. The parameters Pareto front that balances navigational index referring obtained, relevant gliding profile results simulated simultaneously, compared conventional patterns examine quality solution. Comparison shows that, utilization algorithm, voyage performance respect endurance can be effectively improved.