Intelligent path planning method for cooperative traversal task of multiple unmanned vehicles
A path planning and unmanned vehicle technology, applied in vehicle position/route/height control, motor vehicle, two-dimensional position/channel control, etc., can solve the problem of short operating range, small payload and limited operating efficiency of unmanned vehicles And other issues
Active Publication Date: 2021-12-31
ARMY ENG UNIV OF PLA
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However, delivery of parcels to customers is facing new challenges. The short operating range and small payload of unmanned vehicles greatly limit their operating efficiency in the distribution network. Therefore, parcel delivery is expressed as the optimal solution on the map. The path planning problem, which is reduced to the generalized TSP
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[0065] The entire path planning and task allocation process of the present invention includes the following steps, which will be described with reference to the accompanying drawings.
[0066] like figure 1 The intelligent path planning method of multi-drone collaborative traversal task of the present invention includes the following steps:
[0067] Step 1: Design constraint conditions, establish a problem model;
[0068] Step 2: Combine the problem model established in step 1, establish a path planning model;
[0069] Step 3: The path planning model established for step 2, using the collaborative evolutionary hybrid population genetic algorithm search task allocation problem, the synonymous mixing group genetic algorithm is to interact virtual encoding policies, classic evolution methods and mixed crossings The mechanism is combined, search for the optimal solution under multi-constraints, and efficiently constructs the target access sequence for multiple unmanned vehicles.
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The invention discloses an intelligent path planning method for a multi-unmanned vehicle collaborative traversal task, and relates to the technical field of intelligent path planning methods. The method includes the following steps: designing constraint conditions, and establishing a problem model; establishing a path planning model in combination with the established problem model; for the established path planning model, searching the optimal solution of the task allocation problem by using a co-evolutionary hybrid population genetic algorithm, wherein the co-evolutionary hybrid population genetic algorithm combines a virtual coding strategy, a classical evolutionary method and a hybrid crossover mechanism, and the optimal solution is searched under a multi-constraint condition, so that a target access sequence is effectively constructed for multiple unmanned vehicles. According to the method, a path planning model and a thought allocation algorithm are combined, many limitations such as loading capacity and cruising ability are considered, target tasks can be effectively allocated to each unmanned vehicle, and an access sequence can be effectively planned. Compared with a traditional heuristic algorithm, the algorithm has good superiority in the aspects of energy conservation, efficiency and the like.
Description
Technical field [0001] The present invention relates to the technical field of intelligent path planning methods, in particular to intelligent path planning methods for multi-drone collaborative traversal tasks. Background technique [0002] In recent years, due to the extensive application of cargo delivery, relief assistance, environmental monitoring and terrain survey, a single no-car or multiple drones has been widely studied. For example, in a logistics system, the task assignment is to assign a set of drones within the boundary region to different targets or a single drone to access a set of targets in a valid sequence while minimizing the total travel distance or time. [0003] Task allocation issues are variants of Vehicle Routing Problem, VRP and Traveling Salesman Problem (TSP), and the key to TSP is the shortest path to the vehicle design a set of dispersed targets. The purpose of VRP is to transmit the goods to a set of targets using multiple drones, and VRP is a cons...
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IPC IPC(8): G05D1/02
CPCG05D1/0217G05D1/0221G05D1/0287Y02T10/40
Inventor 郭艳周彬李宁王振华刘杰薛端宋晓祥
Owner ARMY ENG UNIV OF PLA