Abstract
This paper addresses the problem of controlling a heterogeneous system composed of multiple Unmanned Aerial Vehicles (UAVs) and Autonomous Underwater Vehicles (AUVs) for formation and containment maintenance. The proposed approach considers actuator time delay and, in addition to formation and containment, considers obstacle avoidance, and offers a robust navigation algorithm and uses a reliable middleware for data transmission and exchange. The methodology followed uses both flocking technique and modified L1 adaptive control to ensure the proper navigation and coordination while avoiding obstacles. The data exchange between all the agents is provided through the data distribution services (DDS) middleware, which solves the interoperability issue when dealing with heterogeneous multiagent systems. The modified L1 controller is a local controller for stabilizing the dynamic model of each UAV and AUV, and the flocking approach is used to coordinate the followers around the leader or within the space delimited by their leaders. Potential Field (PF) allows obstacle avoidance during the agents’ movement. The performance of the proposed approach under the considerations mentioned above are verified and demonstrated using simulations.
Highlights
MotivationThe Unmanned Aerial Vehicle systems (UAVs) and/or Autonomous Underwater Vehicle systems (AUVs) have been involved in numerous applications, including both military and civilian applications such as defense, firefighting, pipeline inspections, exploration, photography, and monitoring
Researchers and engineers are showing great interest in Unmanned Aerial Vehicle systems (UAVs) and/or Autonomous Underwater Vehicle systems (AUVs) systems. This interest is mainly motivated by observable expansions of UAVs and/or AUVs applications, that UAVs are playing a significant role in combating the COVID-19 pandemic [1]
A novel design for heterogeneous formation and containment control has been addressed throughout this paper
Summary
The Unmanned Aerial Vehicle systems (UAVs) and/or Autonomous Underwater Vehicle systems (AUVs) have been involved in numerous applications, including both military and civilian applications such as defense, firefighting, pipeline inspections, exploration, photography, and monitoring. Researchers and engineers are showing great interest in UAVs and/or AUVs systems This interest is mainly motivated by observable expansions of UAVs and/or AUVs applications, that UAVs are playing a significant role in combating the COVID-19 pandemic [1]. Numerous control algorithm designs have been reported in the literature to meet the application criteria either for a group of homogeneous or heterogeneous vehicle systems. The formation containment control designs of multi-leader follower systems have been proposed and reported in [4,5]; the influence of the information transmission between the agents was not considered in the design. DDS middleware has been proposed and designed to overcome the issue of the data loss between multiple UAVs, as well as the interoperability issue associated with heterogeneous systems. Application of the DDS middleware technique augmented with the flocking approach resulted in significant improvements in flexibility, reliability, and portability [8,9]
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