Traditional ant colony algorithm is prone to cause failure by deadlocks in complex environments. A novel method is proposed to solve the problem，which adjusts the heuristic function by introducing environmental factors according to environmental information，increased the number of ants effectively，improved the search speed of ant colony，and expanded the search range. Aiming at the limitation of traditional ant colony algorithm in pursuit of shortest path in the ideal region in path planning，and the shortest path in the multi-factor environment is often not the optimal solution，the multi-objective path planning is proposed based on the weighted optimization of transition probability in different environments on the basis of the shortest path，which enriches the practicality and practical significance of the ant colony algorithm. Finally，the simulation experiment of optimization algorithm proves the feasibility of the method.