DDS-Based Containment Control of Multiple UAV Systems

In this paper, we present a robust containment control design for multi Unmanned Aerial Vehicle Systems (UAVs) based on the Data Distribution Service (DDS) middleware and L 1 adaptive controller. The Data Distribution Service middleware, L 1 adaptive controller and graph theory technique are utilized for the navigation of the UAVs. The L 1 controller is utilized as a local controller for each UAVs and the graph theory approach is utilized to constitute the followers inside their leaders. Finally, the DDS Middleware is used to exchange data between the followers and their leaders. Robust adaptation of the L 1 controller makes the system robust with a high level of performance. Matlab simulation verified the robustness of the L 1 controller. We provide stability proofs using Lyapunov analysis for the UAVs framework.

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Faculty Opinions recommendation of Patch definition in metapopulation analysis: a graph theory approach to solve the mega-patch problem.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718325966.793496160 ◽

2014 ◽

Author(s):

Frédéric Guichard

Keyword(s):

Graph Theory ◽

Theory Approach

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Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽

10.3390/s21072534 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2534

Author(s):

Oualid Doukhi ◽

Deok-Jin Lee

Keyword(s):

Reinforcement Learning ◽

Real Time ◽

Autonomous Navigation ◽

Control Technique ◽

Local Motion ◽

Aerial Robots ◽

Novel Approach ◽

Outdoor Environments ◽

Aerial Vehicle ◽

High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

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Vulnerability Assessment of a Large Electrical Grid by New Graph Theory Approach

IEEE Latin America Transactions ◽

10.1109/tla.2018.8327409 ◽

2018 ◽

Vol 16 (2) ◽

pp. 527-535 ◽

Cited By ~ 10

Author(s):

J. BEYZA ◽

J. M. Yusta ◽

G. J. Correa ◽

H. F. Ruiz

Keyword(s):

Graph Theory ◽

Vulnerability Assessment ◽

Theory Approach ◽

Electrical Grid

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Exploring the full catalytic cycle of rhodium(i)–BINAP-catalysed isomerisation of allylic amines: a graph theory approach for path optimisation

Chemical Science ◽

10.1039/c7sc00401j ◽

2017 ◽

Vol 8 (6) ◽

pp. 4475-4488 ◽

Cited By ~ 13

Author(s):

Takayoshi Yoshimura ◽

Satoshi Maeda ◽

Tetsuya Taketsugu ◽

Masaya Sawamura ◽

Keiji Morokuma ◽

...

Keyword(s):

Graph Theory ◽

Reaction Mechanism ◽

Catalytic Cycle ◽

Theory Approach ◽

Allylic Amines ◽

Reaction Route ◽

Reaction Method ◽

Mapping Strategy ◽

Global Reaction ◽

Induced Reaction

The reaction mechanism of the cationic rhodium(i)–BINAP complex catalysed isomerisation of allylic amines was explored using the artificial force induced reaction method with the global reaction route mapping strategy.

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Conserving woodland caribou habitat while maintaining timber yield: a graph theory approach

Canadian Journal of Forest Research ◽

10.1139/cjfr-2015-0431 ◽

2016 ◽

Vol 46 (7) ◽

pp. 914-923 ◽

Cited By ~ 5

Author(s):

Jonathan L.W. Ruppert ◽

Marie-Josée Fortin ◽

Eldon A. Gunn ◽

David L. Martell

Keyword(s):

Graph Theory ◽

Rangifer Tarandus ◽

High Volume ◽

Timber Harvesting ◽

Optimization Approach ◽

Theory Approach ◽

Heuristic Procedure ◽

Woodland Caribou ◽

Old Growth ◽

Old Growth Forest

The fragmentation and loss of old-growth forest has led to the decline of many forest-dwelling species that depend on old-growth forest as habitat. Emblematic of this issue in many areas of the managed boreal forest in Canada is the threatened woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)). We develop a methodology to help determine when and how timber can be harvested to best satisfy both industrial timber supply and woodland caribou habitat requirements. To start, we use least-cost paths based on graph theory to determine the configuration of woodland caribou preferred habitat patches. We then developed a heuristic procedure to schedule timber harvesting based on a trade-off between merchantable wood volume and the remaining amount of habitat and its connectivity during a planning cycle. Our heuristic can attain 84% of the potential woodland caribou habitat that would be available in the absence of harvesting at the end of a 100 year planning horizon. Interestingly, this is more than that which is attained by the current plan (50%) and a harvesting plan that targets high volume stands (32%). Our results indicate that our heuristic procedure (i.e., an ecologically tuned optimization approach) may better direct industrial activities to improve old-growth habitat while maintaining specified timber production levels.

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