Multi-UAV Oxyrrhis Marina-Inspired Search and Dynamic Formation Control for Forest Firefighting

• Published in: IEEE transactions on automation science and engineering Vol. 16; no. 2; pp. 863 - 873
• Main Authors: Harikumar, K., Senthilnath, J., Sundaram, Suresh
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Angular position; Communication; Computer simulation; Control theory; Decentralized control; Decentralized search; Displacement; Fire fighting; forest firefighting; Forestry; Forests; formation control; Fuels; Heuristic algorithms; Monte Carlo simulation; multi-unmanned aerial vehicle (UAV) system; Oxyrrhis Marina-inspired search (OMS); Performance evaluation; Search algorithms; Search and rescue missions; Sensors; Target recognition; Target tracking; Task analysis; Temperature measurement; Thermal imaging; Tracking; Tracking control; Unmanned aerial vehicles; Vehicle dynamics
• ISSN: 1545-5955; 1558-3783
• DOI: 10.1109/TASE.2018.2867614

This paper presents an Oxyrrhis Marina-inspired search and dynamic formation control (OMS-DFC) framework for multi-unmanned aerial vehicle (UAV) systems to efficiently search and neutralize a dynamic target (forest fire) in an unknown/uncertain environment. The OMS-DFC framework consists of two stages, viz., the target identification stage without communication between UAVs and the mitigation stage with restricted communication. In the first stage, each UAV adapts proposed OMS with three levels to select between Levy flight, Brownian search, and directionally driven Brownian (DDB) search for accurate target identification ("fire location"). The selection of each level is based on the available sensor information about the possible fire location. In the second stage, the UAVs that identified a fire location fly in a dynamic formation to quench the fire using water. The proposed formation is achieved through decentralized control, where a UAV computes the control action based on the fire profile and also the angular position and angular separation with its succeeding neighbor. The proposed formation control law guarantees asymptotic convergence to the desired time-varying angular position profile of UAVs based on the nature of fire spread (circular/elliptical). To evaluate the performance of the proposed OMS-DFC for the multi-UAV system, a search and fire quenching mission in a typical pine forest is simulated. A Monte Carlo simulation study is conducted to evaluate the average performance of the proposed OMS-DFC-based multi-UAV mission, and the results clearly highlight the advantages of the proposed OMS-DFC in forest firefighting. Note to Practitioners -Searching and mitigating dynamic targets like the forest fire is a challenging task due to the large area involved and also the time-varying nature of fire spread. The use of a cooperative multi-unmanned aerial vehicle (UAV) system for searching targets in large area poses difficulties in maintaining persistent long distance communication between them. Moreover, the elliptical fire profile demands a time-varying angular displacement formation control of UAVs for effective fire mitigation. In this paper, we present a two-stage framework for search and mitigation of forest fire. The first stage provides a decentralized, noniterative stochastic search algorithm that requires no information sharing between the UAVs. The proposed search algorithm can be implemented without much computational efforts using a temperature measuring sensor and a thermal imaging sensor. The second stage provides a decentralized time-varying angular displacement formation control law efficient for tracking elliptical targets. The formation control law only assumes the availability of restricted UAV communication. The proposed formation control law can handle any targets that demand time-varying angular displacement formation for UAVs. The proposed algorithm is suitable for multi-UAV missions involving search and mitigation of dynamic targets distributed over a large area.