Multi-UAV Disjoint Areas Inspection

ChoosePath mission planning platform is a tool for on-line multi-UAV mission generation, for inspection operations. This platform incorporates a state-of-the-art multi-robot Coverage Path Planning solution for coverage operations, and the newly introduced multi-UAV Disjoint Areas Inspection (mUDAI) method, for the fast inspection of scattered regions (FISR). This page provides a guide for the use of mUDAI tool inside the platform.

The following image shows the initial page of ChoosePath Platform. On the left column you can find missions stored in the database, while on the right side there is a map, with a search box to find specific locations.

The user can click on the "NEW" button to generate a new mission, and a pop-up box will allow them to select the desired type of mission. In order to plan and generate a mission with the mUDAI algorithm, they have to select the "Scattered Regions Visitation" button, as shown bellow:

Once they select the type, the UI goes to the second page that is for planning the FISR mission. A "Launching Point" appears on the map, corresponding to the location that the user intends to use as launching position for the UAV(s), and the first polygon to define a region of interest (ROI) is initialized. By clicking on "ADD POLYGON" button, the user is able to generate as many ROIs as they desire, and by right clicking on a polygon they can delete it from the map.

Additionally, the user should define the type of UAVs they intend to use, in order to retrieve the camera's specifications, a parameter critical for the optimization procedure for the viewpoints' calculation for each ROI. They are also able to select the number of UAVs they intend to use for the mission. In case the operational duration of the mission exceeds the nominal one of the UAVs used, the algorithm automatically doubles the number of trajectories, to allow the execution of the mission with the available vehicles, by adding an additional task to each of them. In the "ADVANCED" specifications box, the user can define the maximum and the minimum altitudes allowed for the UAVs' capturing positions, the desired constant flight altitude for the transition among viewpoints, the desired speed of the UAVs, as well as the optimization objective that will be used for the calculation of the viewpoints (Maximized Coverage Objective (MCO) - Balanced Coverage Objective (BCO)). The two following images show two example of missions, one for a single UAV, with the "Maximized Coverage" objective, and one for three UAVs, with the "Balanced Coverage" objective.

The user can now store the generated mission in the database. Additionally, ChoosePath platform can be used for the deployment of the missions in the real-world, with the use of an intermediate integration layer for the unmanned vehicles used. The third tab of the platform provides the options for the deployment of the missions, and the capability for the user to track the progress in real time.

The novel mUDAI algorithm, along with a strict definition of the FISR problem are introduced in the following article:
https://doi.org/10.1016/j.robot.2025.105297

Additionally, an open source Python implementation of mUDAI algorithm can be found in this GitHub repo.