Control of Multiple UAVs for Persistent Surveillance: Algorithm Description and Hardware Demonstration

Nigam, Nikhil; Bieniawski, Stefan R.; Kroo, Ilan; Vian, John

doi:10.2514/6.2009-1852

Cited by 14 publications

(16 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Often, the finite horizon limits the look-ahead ability of the planner, while a suitably engineered reactive control "policy" might be able to achieve longer look-ahead. This was illustrated by some of our work, where the reactive policy roughly converts a time extended problem into a single time step problem and outperforms a relatively naive implementation of a planning based method [110].…”

Section: Planningmentioning

confidence: 89%

“…They demonstrate a mission health management system for 24/7 persistent surveillance trying to keep at least one UAV airborne in a target area. The authors of this survey have looked at the other aspect-maintainance of good mission performance in such a scenario [110]. Bethke, Bertuccelli, and How [111] also focus on improving efficiency by finding the optimum health monitoring policy (deciding when the UAVs should land and takeoff) online.…”

Section: Related Workmentioning

confidence: 99%

“…Decentralized approaches on the other hand, are characterized by agents taking sufficiently high level decisions independently [22,98]. There can be some communication between agents (for instance sharing of maps or position information), but is typically not critical for decision making [110]. Typically the approaches using potential field techniques [22], swarm intelligence [75], behavior-based methods [98], and pre-determined search patterns [101] tend to be decentralized.…”

Section: Centralized Vs Decentralized Techniquesmentioning

confidence: 99%

See 2 more Smart Citations

The Multiple Unmanned Air Vehicle Persistent Surveillance Problem: A Review

Nigam

2014

Machines

Self Cite

View full text Add to dashboard Cite

Control of autonomous vehicles for applications such as surveillance, search, and exploration has been a topic of great interest over the past two decades. In particular, there has been a rising interest in control of multiple vehicles for reasons such as increase in system reliability, robustness, and efficiency, with a possible reduction in cost. The exploration problem is NP hard even for a single vehicle/agent, and the use of multiple vehicles brings forth a whole new suite of problems associated with communication and cooperation between vehicles. The persistent surveillance problem differs from exploration since it involves continuous/repeated coverage of the target space, minimizing time between re-visits. The use of aerial vehicles demands consideration of vehicle dynamic and endurance constraints as well. Another aspect of the problem that has been investigated to a lesser extent is the design of the vehicles for particular missions. The intent of this paper is to thoroughly review the persistent surveillance problem, with particular focus on multiple Unmanned Air Vehicles (UAVs), and present some of our own work in this area. We investigate the different aspects of the problem and slightly digress into techniques that have been applied to exploration and coverage, but a comprehensive survey of all the work in multiple vehicle control for search, exploration, and coverage is beyond the scope of this paper.

show abstract

Section: Planningmentioning

confidence: 89%

Section: Related Workmentioning

confidence: 99%

Section: Centralized Vs Decentralized Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

The Multiple Unmanned Air Vehicle Persistent Surveillance Problem: A Review

Nigam

2014

Machines

Self Cite

View full text Add to dashboard Cite

show abstract

“…Once the algorithms are verified in simulation, they can be seamlessly integrated onto the actual hardware for real time operations. This facility has been used previously to validate other strategic, autonomous algorithms using this work flow [17].…”

Section: A Boeing Hardware Environmentmentioning

confidence: 99%

Partitioned searching and deconfliction: Analysis and flight tests

Lum

Vagners

Jang

et al. 2010

Proceedings of the 2010 American Control Conference

View full text Add to dashboard Cite

Searching a complex environment for a hidden target is a common problem encountered by many autonomous systems. Many modern autonomous systems use a hierarchical structure for mission management where different algorithms perform different tasks to give agents desired behavior. This work investigates a search policy that guarantees both an exhaustive search of the map and conflict free paths of all agents. Agents formulate control decisions for a fixed number of time steps using a modular algorithm that allows parameterizations of agent capabilities. High fidelity simulation and flight test data using multiple autonomous vehicles are used to verify and validate the algorithms in real time.

show abstract

“…Different from fixed surveillance cameras that only offer fixed views on a limited region [205], UAV-enabled aerial surveillance can provide flexible views. Some studies investigate the autonomous capabilities of UAV-enabled surveillance, including regions detection [206], [207], objects positioning [149], and path planning [208]- [210]. In addition, there is a strong demand to design an interface for connecting UAVs with the internet; this connection enables the Internet to monitor the UAV states.…”

Section: Intelligent Local Computing Servicesmentioning

confidence: 99%

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Liu

Dai

Wang

et al. 2020

Computer Communications

179

View full text Add to dashboard Cite

The recent advances in information and communication technology (ICT) have further extended Internet of Things (IoT) from the sole "things" aspect to the omnipotent role of "intelligent connection of things". Meanwhile, the concept of internet of everything (IoE) is presented as such an omnipotent extension of IoT. However, the IoE realization meets critical challenges including the restricted network coverage and the limited resource of existing network technologies. Recently, Unmanned Aerial Vehicles (UAVs) have attracted significant attentions attributed to their high mobility, low cost, and flexible deployment. Thus, UAVs may potentially overcome the challenges of IoE. This article presents a comprehensive survey on opportunities and challenges of UAV-enabled IoE. We first present three critical expectations of IoE: 1) scalability requiring a scalable network architecture with ubiquitous coverage, 2) intelligence requiring a global computing plane enabling intelligent things, 3) diversity requiring provisions of diverse applications. Thereafter, we review the enabling technologies to achieve these expectations and discuss four intrinsic constraints of IoE (i.e., coverage constraint, battery constraint, computing constraint, and security issues). We then present an overview of UAVs. We next discuss the opportunities brought by UAV to IoE. Additionally, we introduce a UAV-enabled IoE (Ue-IoE) solution by exploiting UAVs's mobility, in which we show that Ue-IoE can greatly enhance the scalability, intelligence and diversity of IoE. Finally, we outline the future directions in Ue-IoE.

show abstract

Control of Multiple UAVs for Persistent Surveillance: Algorithm Description and Hardware Demonstration

Cited by 14 publications

References 32 publications

The Multiple Unmanned Air Vehicle Persistent Surveillance Problem: A Review

The Multiple Unmanned Air Vehicle Persistent Surveillance Problem: A Review

Partitioned searching and deconfliction: Analysis and flight tests

Unmanned aerial vehicle for internet of everything: Opportunities and challenges

Contact Info

Product

Resources

About