A Proposed System for Multi-UAVs in Remote Sensing Operations

Abstract

This paper proposes the design of the communications, control systems, and navigation algorithms of a multi-UAV system focused on remote sensing operations. A new controller based on a compensator and a nominal controller is designed to dynamically regulate the UAVs’ attitude. The navigation system addresses the multi-region coverage trajectory planning task using a new approach to solve the TSP-CPP problem. The navigation algorithms were tested theoretically, and the combination of the proposed navigation techniques and control strategy was simulated through the Matlab SimScape platform to optimize the controller’s parameters over several iterations. The results reveal the robustness of the controller and optimal performance of the route planner.

A multi‐UAV system for coverage path planning applications with in‐flight re‐planning capabilities

“…These approaches were evaluated through numerical simulations considering that the aircraft has sufficient energy capacity to complete the entire route. Finally, the research presented in Flores Peña et al (2022) addresses this problem using a near optimal TSP‐based solution for the multiple‐area problem. Most of the works in the literature address the problem in simulation due to its implementation complexity.…”

Synchronous Control of a Group of Flying Robots Following a Leader UAV in an Unfamiliar Environment

“…It should be noted, however, that such solutions take up much space on the supporting structure of the drone, and their weight makes it impossible to take on additional cargo. Another approach is the simultaneous monitoring and remote control of each vehicle in the group [ 4 ]. Theoretically, it is possible to plan a trajectory for multiple drones in a constraint area [ 5 ].…”

A multi-UAV system for coverage path planning applications with in-flight re-planning capabilities

“…These approaches were evaluated through numerical simulations considering that the aircraft has sufficient energy capacity to complete the entire route. Finally, the research presented in (Flores Peña et al, 2022) addresses this problem using a near optimal TSP-based solution for the multiple-area problem.…”

“…The algorithm repeats the process until all the routes are added to W . This computationally efficient heuristic solution is a near-optimal alternative for the multiple areas visiting order problem, but unlike other works in the literature (Vasquez-Gomez et al, 2018;Xie and Chen, 2022;Flores Peña et al, 2022), this technique does not globally optimize the total distance traveled; which means that the mission cost can increase if the number of regions increases significantly. However, as shown in the results in Section 5, the computation time is reduced.…”