Multi-UAV routing for persistent intelligence surveillance &amp; reconnaissance missions

Manyam, Satyanarayana G.; Rasmussen, Steven J.; Casbeer, David W.; Kalyanam, K.M.; Manickam, Suresh

doi:10.1109/icuas.2017.7991314

Cited by 76 publications

(47 citation statements)

References 16 publications

(34 reference statements)

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“…UAVs change batteries at base stations, and the planning horizon is determined by the available number of batteries. Manyam et al [25] consider also the data delivery latency to the base station. Keller et al [26] present a tour planning approach taking into account turning radius constraints of gliders.…”

Section: Sensing Robot Connectivitymentioning

confidence: 99%

Multi-Robot Persistent Surveillance With Connectivity Constraints

Scherer

Rinner

2020

IEEE Access

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Mobile robots, especially unmanned aerial vehicles (UAVs), are of increasing interest for surveillance and disaster response scenarios. We consider the problem of multi-robot persistent surveillance with connectivity constraints where robots have to visit sensing locations periodically and maintain a multihop connection to a base station. We formally define several problem instances closely related to multi-robot persistent surveillance with connectivity constraints, i.e., connectivity-constrained multirobot persistent surveillance (CMPS), connectivity-constrained multi-robot reachability (CMR), and connectivity-constrained multi-robot reachability with relay dropping (CMRD), and show that they are all NP-hard on general graph. We introduce three heuristics with different planning horizons for convex grid graphs and combine these with a tree traversal approach which can be applied to a partitioning of non-convex grid graphs (CMPS with tree traversal, CMPSTT). In simulation studies we show that a short horizon greedy approach, which requires parameters to be optimized beforehand, can outperform a full horizon approach, which requires a tour through all sensing locations, if the number of robots is larger than the minimum number of robots required to reach all sensing locations. The minimum number required is the number of robots necessary for building a chain to the farthest sensing location from the base station. Furthermore, we show that partitioning the area and applying the tree traversal approach can achieve a performance similar to the unpartitioned case up to a certain number of robots but requires less optimization time.

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Section: Sensing Robot Connectivitymentioning

confidence: 99%

Multi-Robot Persistent Surveillance With Connectivity Constraints

Scherer

Rinner

2020

IEEE Access

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“…Persistent Intelligence, Surveillance and Reconnaissance (PISR) routing problem are also considered by minimizing the time of delivering the collected data to the control station (Manyam et al, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Two-Echelon Routing Problem for Parcel Delivery by Cooperated Truck and Drone

Liu¹,

Shi²,

Wu³

et al. 2019

Preprint

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A new variant of two-echelon routing problem is investigated, where the truck and the drone are used to cooperatively complete the deliveries of all parcels. The truck not only acts as a tool for parcel delivery, but also serves as a moving depot for the drone. The drone can carry several parcels and take off from the truck, while returning to the truck after completing the delivery. The energy consumption model for the routing process of the drone is analyzed, when it is utilized to deliver multiple parcels. A two-stage route-based modelling approach is proposed to optimize both the truck’s main route and the drone’s adjoint flying routes. A hybrid heuristic integrating nearest neighbor and cost saving strategies is developed to quickly construct a feasible solution. The simulated annealing algorithm is applied to improve the quality of the solution, where a Tabu list is employed to improve the search efficiency. Random instances at different scales are used to test the performance of the proposed algorithm. A case study based on the practical road network in Changsha, China, is presented, through which the sensitivity analysis is conducted with respect to some critical factors.

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“…Moreover, Avellar, Gustavo S. C, et al [21] present a solution for the problem of using a group of unmanned air vehicles (UAVs) equipped with image sensors to gather intelligence information, which the objective is to minimum time coverage of ground areas. Persistent Intelligence, Surveillance and Reconnaissance (PISR) routing problem are also considered by minimizing the time of delivering the collected data to the control station [2]. Unfortunately, most of these researches are based on the traditional routing problem, with little touch and exploration on the optimization of base location and flight path.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Border patrol is one of military Intelligence, Surveillance and Reconnaissance (ISR) missions. In many ISR missions especially monitoring mission, Unmanned Aerial Vehicles (UAVs) have become a natural choice with the deployment of air surveillance technology [1,2]. In border patrol, some areas located on or inside the borderline where have the high rates of illegal activities would be focused.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance and Reconnaissance

Liu¹,

Liu²,

Shi³

et al. 2019

Preprint

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The location routing problem of unmanned aerial vehicles (UAV) in border patrol for intelligence, surveillance and reconnaissance is investigated, where the location of UAV base stations and the UAV flying routes for visiting the targets in border area are jointly optimized. The capacity of the base station and the endurance of the UAV are considered. A binary integer programming model is developed to formulate the problem, and two heuristic algorithms combined with local search strategies are designed for solving the problem. The experiment design for simulating the distribution of stations and targets in border is proposed for generating random test instances. Also, an example based on the Sino-Vietnamese border is presented to illustrate the problem and the solution approach. The performance of the two algorithms are analyzed and compared through randomly generated instances.

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Multi-UAV routing for persistent intelligence surveillance & reconnaissance missions

Cited by 76 publications

References 16 publications

Multi-Robot Persistent Surveillance With Connectivity Constraints

Multi-Robot Persistent Surveillance With Connectivity Constraints

Two-Echelon Routing Problem for Parcel Delivery by Cooperated Truck and Drone

Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance and Reconnaissance

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