An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles

Cunningham, C T; Roberts, R S

doi:10.1109/ROBOT.2001.933238

Title: An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles

Full Record
Other Related Research

Abstract

An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.

Authors:: Cunningham, C T; Roberts, R S

Publication Date:: Tue Sep 12 00:00:00 EDT 2000

Research Org.:: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Sponsoring Org.:: USDOE Office of Defense Programs (DP) (US)

OSTI Identifier:: 790394

Report Number(s):: UCRL-JC-140415
TRN: US200304%%487

DOE Contract Number:: W-7405-Eng-48

Resource Type:: Conference

Resource Relation:: Journal Volume: 4; Conference: 2001 Institute of Electrical and Electronics Engineers Conference on Robotics and Automation, Seoul (KR), 05/21/2001--05/26/2001; Other Information: PBD: 12 Sep 2000

Country of Publication:: United States

Language:: English

Subject:: 42 ENGINEERING; AIR; ALGORITHMS; AUTOMATION; ENGINEERS; PLANNING; AIRCRAFT

Citation Formats


                    Cunningham, C T, and Roberts, R S. An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles.  United States: N. p., 2000. 
        Web.  doi:10.1109/ROBOT.2001.933238.

Copy to clipboard


                    Cunningham, C T, & Roberts, R S. An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles.  United States.  https://doi.org/10.1109/ROBOT.2001.933238

Copy to clipboard


                    Cunningham, C T, and Roberts, R S. 2000.  
        "An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles".  United States.  https://doi.org/10.1109/ROBOT.2001.933238.  https://www.osti.gov/servlets/purl/790394.

Copy to clipboard


                    
@article{osti_790394,

  title        = {An Adaptive Path Planning Algorithm for Cooperating Unmanned Air Vehicles},

  author       = {Cunningham, C T and Roberts, R S},

  abstractNote = {An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.},

  doi          = {10.1109/ROBOT.2001.933238},

  url          = {https://www.osti.gov/biblio/790394},
  journal      = {},
number       = ,

  volume       = 4,

  place        = {United States},

  year         = {Tue Sep 12 00:00:00 EDT 2000},

  month        = {Tue Sep 12 00:00:00 EDT 2000}

}

Copy to clipboard

Conference:

View Conference (0.65 MB)

https://doi.org/10.1109/ROBOT.2001.933238

Other availability

Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:

Export Metadata

Save to My Library

Similar records in OSTI.GOV collections:

Adaptive path planning algorithm for cooperating unmanned air vehicles

Conference Cunningham, C; Roberts, R

An adaptive path planning algorithm is presented for cooperating Unmanned Air Vehicles (UAVs) that are used to deploy and operate land-based sensor networks. The algorithm employs a global cost function to generate paths for the UAVs, and adapts the paths to exceptions that might occur. Examples are provided of the paths and adaptation.
https://doi.org/10.1109/ROBOT.2001.933238

Full Text Available
UAV Cooperation Architectures for Persistent Sensing

Conference Roberts, R; Kent, C; Jones, E

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore »« less
https://doi.org/10.1117/12.485922

Full Text Available
Cooperative Routing for an Air–Ground Vehicle Team—Exact Algorithm, Transformation Method, and Heuristics

Journal Article Manyam, Satyanarayana; Sundar, Kaarthik; Casbeer, David - IEEE Transactions on Automation Science and Engineering

This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomlymore »« less
https://doi.org/10.1109/tase.2019.2931894

Full Text Available
Algorithms for Heterogeneous, Multiple Depot, Multiple Unmanned Vehicle Path Planning Problems

Journal Article Sundar, Kaarthik; Rathinam, Sivakumar - Journal of Intelligent & Robotic Systems

Unmanned vehicles, both aerial and ground, are being used in several monitoring applications to collect data from a set of targets. This article addresses a problem where a group of heterogeneous aerial or ground vehicles with different motion constraints located at distinct depots visit a set of targets. The vehicles also may be equipped with different sensors, and therefore, a target may not be visited by any vehicle. The objective is to find an optimal path for each vehicle starting and ending at its respective depot such that each target is visited at least once by some vehicle, the vehicle–targetmore »« less
Cited by 27
https://doi.org/10.1007/s10846-016-0458-5

Full Text Available
Unmanned air vehicle (UAV) ultra-persitence research

Program Document Dron, S

Sandia National Laboratories and Northrop Grumman Corporation Integrated Systems, Unmanned Systems (NGIS UMS) collaborated to further ultra-persistence technologies for unmanned air vehicles (UAVs). The greatest shortfalls in UAV capabilities have been repeatedly identified as (1) insufficient flight persistence or 'hang time,' (2) marginal electrical power for running higher power avionics and payload systems, and (3) inadequate communications bandwidth and reach. NGIS UMS requested support from Sandia to develop an ultra-persistent propulsion and power system (UP3S) for potential incorporation into next generation UAV systems. The team members tried to determine which energy storage and power generation concepts could most effectively pushmore »« less
Full Text Available

Similar Records