Fire fighting truck path planning method and system, terminal and storage medium

Abstract

The invention discloses a fire fighting truck path planning method and system, a terminal and a storage medium. The method comprises the following steps: acquiring an environment model; based on the environment model, obtaining search boundary information and obstacle information, and adopting a target trend rapid expansion tree to carry out search to obtain a global path; based on the global path, sending a control signal to the fire fighting truck, so that the fire fighting truck moves to a target point from a fire truck garage along the global path; receiving fixed obstacle information fed back in the walking process of the fire fighting truck, and correcting the current pose of the fire fighting truck based on the received fixed obstacle pose; receiving dynamic obstacle information fed back in the walking process of the fire fighting truck, carrying out obstacle movement collision prediction based on the received dynamic obstacle, determining whether local path planning is conducted or not based on the prediction result, and updating the global path through the local path planning. According to the method and system, the optimal path can be quickly searched, obstacle avoidance planning can be carried out on dynamic obstacles, and the fire fighting truck is controlled to safely arrive at the target point without collision.

Description

technical field [0001] The invention belongs to the technical field of route planning, and in particular relates to a fire truck route planning method, system, terminal and storage medium. Background technique [0002] With the continuous progress and development of science and technology, robot technology has been applied in fire protection, but in the actual application process, intelligent control technology has not been well demonstrated. For fire-fighting robots, efficient planning of a collision-free and safe path from the starting point to the fire-fighting point is the basis of intelligence and an important part of intelligent fire-fighting robots. In the traditional path planning methods, the common ones are grid map search method, particle swarm optimization algorithm and fast random tree search method. However, the grid map search method is easy to construct, but the route planning efficiency is low and the space is wasted, and the resolution of the grid does not...

AI Technical Summary

Problems solved by technology

The fast expanding tree algorithm is to limit the maximum rotation angle to explore random points, which limits the search direction and range, and is prone to local unsolvability, and the simple environment model cannot quickly search and reach the target point; establish a dynamic window detection to avoid local obstacles of dynamic obstacles Planning, there is no motion prediction for dynamic obstacles, resulting in uncertain dynamic obstacle environment models, and the path obtained by local planning cannot avoid obstacles; the real-time pose of the robot is obtained through the odometer, and there is a sliding error, and the pose is not corrected. There is an error in the initial point of the local planning, resulting in poor dynamic obstacle avoidance planning effect

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