Multi-vehicle cooperative handling formation optimization method based on improved genetic algorithm

In order to improve the safety of the multi-vehicle collaborative handling process and the flexibility of mobile robot scheduling, this paper optimizes the design of target formations for different types of mobile robots to carry heavy objects well. Rolling moment, combined with the handling strategy, a multi-vehicle intact heavy object handling model was established. At the same time, the energy-based static stability description method ESM (Energy Stability Margin) and the spacing between each short-circuit mobile robot are introduced to evaluate the team's search for the optimal form through an improved genetic algorithm, and the initial population generation method and selection methods, crossover and mutation methods; finally, the advantages and disadvantages of the form proposed in this article are proved through example verification and comparison with traditional genetic algorithms. The algorithm for solving multi-vehicle collaborative handling teams optimizes suction and perception problems.