The definition of virtual obstacles for high temperature heat sources was proposed in order to solve the safety and efficiency problems faced by the global path planning of mobile robots in high temperature scenarios. A hybrid obstacle space model was established. The path planning problem in high temperature scene was transformed into a multi-objective optimization problem in high temperature mixed obstacle space, which considered the cost of path temperature and length. The NSGA-Ⅱ algorithm was improved to expand the population by selecting excellent non-feasible solutions, which improved the population diversity and population evolution efficiency. A new adaptive crossover and mutation probability calculation method was proposed. The process adjustment value realized the balance between the search ability in the early stage of the population and the convergence in the later stage according to the individual cost function value and the overall evolution process of the population. The simulation results of the optimal path show that although the path length cost of the proposed improved algorithm is slightly higher than that of the original algorithm and other improved algorithms, the temperature cost is greatly reduced. The proposed improved algorithm is more effective to avoid falling into the local optimal solution.