Abstract: Indoor route planning is affected by a variety of constraints. When considering the spatial geometry and environmental attribute information of the scene, it is also necessary to take into account the application preferences, isotropic characteristics of indoor route-finding behavior, and the effects of superimposed multiple constraints on route-finding. This requires a data model that can integrate multiple constraints to model indoor scenes. Therefore, a multi-factor constrained A^* algorithm model based on a hexagonal grid is constructed. This algorithm uses an isotropic regular hexagon to model the indoor scene, and uses the constraints as the factors to guide the route-finding algorithm to achieve route planning. Based on this model, and taking distance, recognition, and pedestrian density as examples, the influence of constraints on route planning is illustrated, and the superiority of organic combination with scene modeling and routefinding algorithms is explained. The experimental results show that the scheme can effectively take into account the constraints such as distance, landmark intensity, and pedestrian heat, and provide a route more in line with application preferences.