Abstract: Multi-robot mission planning is one of the main problems in multi-robot system research. Multi-objective multi-robot mission planning refers to optimizing multiple indicators of the multi-robot system at the same time. In recent years, heuristic algorithms have increasingly been used to solve multi-objective prob-lems. In this paper, a multi-objective multi-robot mission planning method based on improved fireworks algorithm was proposed. In addition, the sorting method and selection strategy of the multi-objective so-lutions were discussed in detail. In order to verify the performance of the method, seven instances were tested, and the method was compared with other four multi-objective algorithms on the S-metric index. The other four multi-objective algorithms were Non-dominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm 2 (SPEA2)，Pareto Envelope-based Selection Algorithm (PESA) and an Improved Strength Pareto Genetic Algorithm 2 (SPGA2). Experimental results shown that the proposed multi-objective multi-robot mission planning method based on improved fireworks algorithm has obvious advantages both in Pareto solution set quality and solution set scale.