Artificial Intelligence Methodologies Applicable to Support the Decision-Making Capability on Board Unmanned Aerial Vehicles

2008 ◽  
Author(s):  
Isabella Panella
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles

scholarly journals Selection of Unmanned Aerial Vehicles by Using Multicriteria Decision-Making for Defence

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Mustafa Hamurcu ◽  
Tamer Eren
Keyword(s):  
Decision Making ◽  
Unmanned Aerial Vehicles ◽  
Selection Process ◽  
Critical Role ◽  
Multicriteria Decision Making ◽  
Critical Factor ◽  
Unmanned Systems ◽  
Multicriteria Decision ◽  
Aerial Vehicles ◽  
Selection Of

The unmanned systems have been seeing a significant boom in the last ten years in different areas together with technological developments. One of the unmanned systems is unmanned aerial vehicles (UAVs). UAVs are used for reconnaissance and observation in the military areas and play critical role in attack and destroy missions. These vehicles have been winning more features together with developing technology in todays world. In addition, they have been varying with different features. A systematic and efficient approach for the selection of the UAV is necessary to choose a best alternative for the critical tasks under consideration. The multicriteria decision-making (MCDM) approaches that are analytic processes are well suited to deal intricacy in selection of alternative vehicles. This study also proposes an integrated methodology based on the analytic hierarch process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to evaluate UAV alternatives for selection process. Firstly, AHP, a MCDM method, is used to determine the weights of each critical factor. Subsequently, it is utilized with the TOPSIS approach to rank the vehicle alternatives in the decision problem. Result of the study shows that UAV-1 was selected as the most suitable vehicle. In results, it is seen that the weights of the evaluation criteria found by using AHP affect the decision-making process. Finally, the validation and sensitivity analysis of the solution are made and discussed.

scholarly journals Evolving Rule-Based Explainable Artificial Intelligence for Unmanned Aerial Vehicles

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 17001-17016 ◽  
Author(s):  
Blen M. Keneni ◽  
Devinder Kaur ◽  
Ali Al Bataineh ◽  
Vijaya K. Devabhaktuni ◽  
Ahmad Y. Javaid ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Unmanned Aerial Vehicles ◽  
Rule Based ◽  
Aerial Vehicles ◽  
Explainable Artificial Intelligence

scholarly journals A decision-making framework for safe operations of unmanned aerial vehicles in urban scenarios

2020 ◽  
Vol 12 (1) ◽  
pp. 11
Author(s):  
Marcos Quiñones ◽  
Timothy Darrah ◽  
Gautam Biswas ◽  
Chetan Kulkarni
Keyword(s):  
Decision Making ◽  
Unmanned Aerial Vehicles ◽  
Environmental Conditions ◽  
System Performance ◽  
Trajectory Optimization ◽  
Contingency Management ◽  
The State ◽  
Urban Mobility ◽  
Aerial Vehicles ◽  
Number Of Factors

This paper presents a decision-making scheme at the level of individual unmanned aerial vehicles (UAVs) with the goal of maintaining safe operations for urban mobility. The decision-making approach for a single UAV will consider the risks associated with the current trajectory given the existing environmental conditions and the state of the vehicle. The proposed scheme combines the analysis of system performance, environmental conditions, and mission level parameters for contingency management, i.e., make a determination on: (1) to abort mission and land safely; (2) re-plan current mission in full or abbreviated form; and (3) change mission.  A path planning and trajectory optimization algorithm with the goal of minimizing the overall risk of mission failure by considering a number of factors such as the uncertainties in the environment and operating state of the vehicle is proposed. We will consider the mission failure as the loss of control of the vehicle resulting in a collision with other objects or a crash into the ground. An offline part of the framework generates an initial mission plan by considering the state of the vehicle, the environmental, conditions, and the static features of a map of the environment. Once the vehicle takes off, the risk of mission’ failure associated with the remaining trajectory is re-computed in an online framework to assess whether re-planning is required or not. A key challenge that we consider in this paper is to study the effects of multiple interacting subsystems of the UAV on system performance, especially under degraded conditions.

scholarly journals Secure UAV-Based System to Detect Small Boats Using Neural Networks

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Moisés Lodeiro-Santiago ◽  
Pino Caballero-Gil ◽  
Ricardo Aguasca-Colomo ◽  
Cándido Caballero-Gil
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Image Processing ◽  
Deep Learning ◽  
Unmanned Aerial Vehicles ◽  
High Sensitivity ◽  
Search And Rescue ◽  
Detection Systems ◽  
Aerial Vehicles ◽  
Current Detection

This work presents a system to detect small boats (pateras) to help tackle the problem of this type of perilous immigration. The proposal makes extensive use of emerging technologies like Unmanned Aerial Vehicles (UAV) combined with a top-performing algorithm from the field of artificial intelligence known as Deep Learning through Convolutional Neural Networks. The use of this algorithm improves current detection systems based on image processing through the application of filters thanks to the fact that the network learns to distinguish the aforementioned objects through patterns without depending on where they are located. The main result of the proposal has been a classifier that works in real time, allowing the detection of pateras and people (who may need to be rescued), kilometres away from the coast. This could be very useful for Search and Rescue teams in order to plan a rescue before an emergency occurs. Given the high sensitivity of the managed information, the proposed system includes cryptographic protocols to protect the security of communications.

scholarly journals Special Issue on Unmanned Aerial Vehicles (UAVs)

2020 ◽  
Vol 10 (22) ◽  
pp. 8078
Author(s):  
Sunghun Jung
Keyword(s):  
Applied Sciences ◽  
Artificial Intelligence ◽  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Acceptance Rate ◽  
Special Issue ◽  
Aerial Vehicles ◽  
Machine Interface ◽  
Communication Control

This editorial paper was a special issue of Applied Sciences belonging to the section of mechanical engineering in MDPI journal and summarized the collected manuscripts regarding the unmanned aerial vehicles (UAVs) related technologies, including communication, control, collision avoidance, modeling, path planning, human-machine interface (HMI), artificial intelligence (AI), etc. Chronologically, this special issue was started to be coordinated at the end of Oct 2018, prepared for a month and opened to collect manuscripts from the middle of Nov 2018 until the end of Dec 2019. During almost a year, 26 papers were published online out of 50 submitted papers which results in 52% acceptance rate.

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