Mobile Robot Path Planning With Vehicle Deployment Optimization

The path optimization problem is segmented into two distinct stages: (1) path optimization calculation that determines optimal routes between locations, and (2) vehicle deployment optimization that determines the number of vehicles needed. This segmentation allows each sub-problem to be solved independently with appropriate algorithms, improving overall accuracy without exponentially increasing complexity.

An intermediary optimization module is introduced between path calculation and final path planning. This module takes path data and vehicle deployment requirements as inputs, performs coordinated optimization considering both factors, and outputs optimized path plans. The intermediary handles the complexity of joint optimization without requiring complete redesign of the entire system.

Preliminary path optimization is performed before vehicle deployment optimization. The path optimization module pre-calculates optimal routes between all location pairs and stores them. During subsequent vehicle deployment optimization, these pre-calculated paths are reused, avoiding redundant calculations and reducing overall computation time while maintaining accuracy.

The optimization process uses periodic iteration with early stopping criteria. The system performs iterative optimization but monitors convergence metrics, automatically stopping when improvement falls below a threshold or a maximum iteration count is reached. This periodic action with exit conditions prevents excessive computation time while ensuring sufficient optimization accuracy.