Efficient communication-aware dynamic coverage using space-filling curves

Yuan, Yan; Mostofi, Yasamin

doi:10.1109/acc.2014.6859423

Cited by 8 publications

(2 citation statements)

References 26 publications

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“…Similarly irrelevant are approaches that plan for moving targets, not just moving remote sensing platform i.e. dynamic coverage [27], [28].…”

Section: Prior Literaturementioning

confidence: 99%

An Efficient Approach to Communication-aware Path Planning for Long-range Surveillance Missions undertaken by UAVs

Sharma,

Sebastian

2017

Preprint

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While using drones (UAVs) for remote surveillance missions, it is mandatory to do path planning of the vehicle since these are pilot-less vehicles. Path planning, whether offline (more popular) or online, entails setting up the path as a sequence of locations in the 3D Euclidean space, whose coordinates happen to be latitude, longitude and altitude. For the specific application of remote surveillance of long linear infrastructures in non-urban terrain, the continuous 3D-ESP (Euclidean Shortest path) problem practically entails two important scalar costs. The first scalar cost is the distance travelled along the planned path. Since drones are battery operated, hence it is needed that the path length between fixed start and goal locations of a mission should be minimal at all costs. The other scalar cost is the cost of transmitting the acquired video during the mission of remote surveillance, via a camera mounted in the drone's belly. Because of the length of surveillance target which is long linear infrastructure, the amount of video generated is very high and cannot be generally stored in its entirety, on board. If the connectivity is poor along certain segments of a naive path, to boost video transmission rate, the transmission power of the signal is kept high, which in turn dissipates more battery energy. Hence a path is desired that simultaneously also betters what is known as "communication" cost. These two costs trade-off, and hence Pareto optimization is needed for this 3D biobjective Euclidean shortest path problem. In this report, we study the mono-objective offline path planning problem, based on the distance cost, while posing the communication cost as an upper-bounded constraint. The biobjective path planning solution is presented separately in a companion report.

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“…Similarly irrelevant are approaches that plan for moving targets, not just moving remote sensing platform i.e. dynamic coverage [27], [28].…”

Section: Prior Literaturementioning

confidence: 99%

An Efficient Approach to Communication-aware Path Planning for Long-range Surveillance Missions undertaken by UAVs

Sharma,

Sebastian

2017

Preprint

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“…In Jaleel et al (2014), the authors proposed a strategy to minimize motion and communication energy in the case of transmitting sensor information from a given object to a remote station. Yan and Mostofi (2014) designed the motion and communication strategies of the robots such that they periodically visit the points of interest, communicate the gathered information to a remote station, minimize their total energy costs, including motion, sensing and communication energy, and satisfy other system constraints. In their problem, a team of mobile robots needs to cover a set of time-varying points of interest, while maintaining their connectivity to a remote station in a realistic communication environment.…”

mentioning

confidence: 99%

Planning, scheduling and coordination for refuel scheduling on aisle graphs

Gao

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Multi-objective drone path planning for search and rescue with quality-of-service requirements

et al. 2020

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We incorporate communication into the multi-UAV path planning problem for search and rescue missions to enable dynamic task allocation via information dissemination. Communication is not treated as a constraint but a mission goal. While achieving this goal, our aim is to avoid compromising the area coverage goal and the overall mission time. We define the mission tasks as: search, inform, and monitor at the best possible link quality. Building on our centralized simultaneous inform and connect (SIC) path planning strategy, we propose two adaptive strategies: (1) SIC with QoS (SICQ): optimizes search, inform, and monitor tasks simultaneously and (2) SIC following QoS (SIC+): first optimizes search and inform tasks together and then finds the optimum positions for monitoring. Both strategies utilize information as soon as it becomes available to determine UAV tasks. The strategies can be tuned to prioritize certain tasks in relation to others. We illustrate that more tasks can be performed in the given mission time by efficient incorporation of communication in the path design. We also observe that the quality of the resultant paths improves in terms of connectivity.

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Efficient communication-aware dynamic coverage using space-filling curves

Cited by 8 publications

References 26 publications

An Efficient Approach to Communication-aware Path Planning for Long-range Surveillance Missions undertaken by UAVs

An Efficient Approach to Communication-aware Path Planning for Long-range Surveillance Missions undertaken by UAVs

Planning, scheduling and coordination for refuel scheduling on aisle graphs

Multi-objective drone path planning for search and rescue with quality-of-service requirements

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