Distributed Planning Strategies to Ensure Network Connectivity for Dynamic Heterogeneous Teams

Ponda, Sameera S.; Johnson, Luke B.; Kopeikin, Andrew; Choi, Han‐Lim; How, Jonathan P.

doi:10.1109/jsac.2012.120603

Cited by 73 publications

(37 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Besides dynamically keeping vehicles in range and appropriate position to maintain communication relay, artificial potential field based path planning also provides collision avoidance system. Ponda [15] presents a cooperative distributed planning algorithm that ensures network connectivity for a team of heterogeneous agents operating in dynamic and communication limited environments. The algorithm predicts the network topology and to propose relay tasks to repair connectivity violations.…”

Section: B Mobile Relay Motion Control Problemmentioning

confidence: 99%

Using multiple unmanned aerial vehicles to maintain connectivity of MANETs

Zhu

Cai

Zhao

et al. 2014

2014 23rd International Conference on Computer Communication and Networks (ICCCN)

View full text Add to dashboard Cite

Unmanned Aerial Vehicles (UAVs) have emerged as promising relay platforms to improve the connectivity of ground Mobile Ad Hoc Networks (MANETs). Due to the relatively high cost of UAVs, a lot of efforts have been made to optimize the deployment of UAVs so that the number of UAVs needed in maintaining the connectivity of ground nodes can be minimized. However, existing work on optimization of UAVs' deployment hasn't considered the situation that there are already some UAVs deployed in the field. In this paper, we study the problem of deploying minimum number of UAVs to maintain the connectivity of ground MANETs under the condition that some UAVs have already been deployed in the field. We formulate this problem as a Minimum Steiner Tree problem with Existing Mobile Steiner points under Edge Length Bound constraints (MST-EMSELB) and prove that the problem is NP-Complete. We also propose an Existing UAVs Aware (EUA) polynomial time approximate algorithm for the MST-EMSELB problem that uses a maximum match heuristic to compute new positions for existing UAVs. Simulation results demonstrate that the proposed EUA method has bester performance than a non-EUA method in the term of needed new UAV numbers. Compared with the non-EUA method, the EUA method can reduce at most 60% of the new UAVs number.

show abstract

Section: B Mobile Relay Motion Control Problemmentioning

confidence: 99%

Using multiple unmanned aerial vehicles to maintain connectivity of MANETs

Zhu

Cai

Zhao

et al. 2014

2014 23rd International Conference on Computer Communication and Networks (ICCCN)

View full text Add to dashboard Cite

show abstract

“…The score c ij that agent i obtains by performing task j is a function of the value of the task, the cost of execution (e.g. fuel consumed), and the execution time τ ij compared to the optimal task execution time [16].…”

Section: B Task Allocationmentioning

confidence: 99%

“…The tasks dependent on the deleted relays are then placed in the bidding agent's forbidden task list to ensure that the CBBA with Relays algorithm eventually converges on a task assignment solution. Interested readers are referred to [16] for more information.…”

Section: Task Allocation For Network Controlmentioning

confidence: 99%

Multi-UAV network control through dynamic task allocation: Ensuring data-rate and bit-error-rate support

Kopeikin

Ponda

Johnson

et al. 2012

2012 IEEE Globecom Workshops

Self Cite

View full text Add to dashboard Cite

Abstract-A multi-UAV system relies on communications to operate. Failure to communicate remotely sensed mission data to the base may render the system ineffective, and the inability to exchange command and control messages can lead to system failures. This paper describes a unique method to control communications through distributed task allocation to engage under-utilized UAVs to serve as communication relays and to ensure that the network supports mission tasks. The distributed algorithm uses task assignment information, including task location and proposed execution time, to predict the network topology and plan support using relays. By explicitly coupling task assignment and relay creation processes the team is able to optimize the use of agents to address the needs of dynamic complex missions. The framework is designed to consider realistic network communication dynamics including path loss, stochastic fading, and information routing. The planning strategy is shown to ensure that agents support both datarate and interconnectivity bit-error-rate requirements during task execution. System performance is characterized through experiments both in simulation and in outdoor flight testing with a team of three UAVs.

show abstract

“…Given their relative safety and cost-effectiveness, these quadrotors are also being used extensively in indoor flight facilities [9]- [12]. However, current battery technology only enables flights of 8-15 min (depending on vehicle, payload, and wind conditions) for a typical quadrotor [9], [13], which constrains the mission and experimental capabilities of these small-scale UAVs. To enable the capability of sustaining persistent missions, and, in the process, enable research concerned with developing autonomous planning and learning algorithms that depend on data obtained from long-term operations, there is a need to develop a system that can sustain long duration flight.…”

Section: Introductionmentioning

confidence: 99%

An Automated Battery Management System to Enable Persistent Missions With Multiple Aerial Vehicles

Üre

Chowdhary

Toksoz

et al. 2015

IEEE/ASME Trans. Mechatron.

Self Cite

116

View full text Add to dashboard Cite

This paper presents the development and hardware implementation of an autonomous battery maintenance mechatronic system that significantly extends the operational time of battery powered small-scaled unmanned aerial vehicles (UAVs). A simultaneous change and charge approach is used to overcome the significant downtime experienced by existing charge-only approaches. The automated system quickly swaps a depleted battery of a UAV with a replenished one while simultaneously recharging several other batteries. This results in a battery maintenance system with low UAV downtime, arbitrarily extensible operation time, and a compact footprint. Hence, the system can enable multiagent UAV missions that require persistent presence. This capability is illustrated by developing and testing in flight a centralized autonomous planning and learning algorithm that incorporates a probabilistic health model dependent on vehicle battery health that is updated during the mission, and replans to improve the performance based on the improved model. Flight test results are presented for a 3-h-long persistent mission with three UAVs that each has an endurance of 8-10 min on a single battery charge (more than 100 battery swaps).Index Terms-Battery management systems, learning (artificial intelligence), Markov processes, multiagent systems, unmanned aerial vehicles (UAVs).

show abstract

Distributed Planning Strategies to Ensure Network Connectivity for Dynamic Heterogeneous Teams

Cited by 73 publications

References 17 publications

Using multiple unmanned aerial vehicles to maintain connectivity of MANETs

Using multiple unmanned aerial vehicles to maintain connectivity of MANETs

Multi-UAV network control through dynamic task allocation: Ensuring data-rate and bit-error-rate support

An Automated Battery Management System to Enable Persistent Missions With Multiple Aerial Vehicles

Contact Info

Product

Resources

About