2,499 research outputs found
Optimal scheduling for refueling multiple autonomous aerial vehicles
The scheduling, for autonomous refueling, of multiple unmanned aerial vehicles (UAVs) is posed as a combinatorial optimization problem. An efficient dynamic programming (DP) algorithm is introduced for finding the optimal initial refueling sequence. The optimal sequence needs to be recalculated when conditions change, such as when UAVs join or leave the queue unexpectedly. We develop a systematic shuffle scheme to reconfigure the UAV sequence using the least amount of shuffle steps. A similarity metric over UAV sequences is introduced to quantify the reconfiguration effort which is treated as an additional cost and is integrated into the DP algorithm. Feasibility and limitations of this novel approach are also discussed
Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph
Police SWAT teams and Military Special Forces face mounting pressure and
challenges from adversaries that can only be resolved by way of ever more
sophisticated inputs into tactical operations. Lethal Autonomy provides
constrained military/security forces with a viable option, but only if
implementation has got proper empirically supported foundations. Autonomous
weapon systems can be designed and developed to conduct ground, air and naval
operations. This monograph offers some insights into the challenges of
developing legal, reliable and ethical forms of autonomous weapons, that
address the gap between Police or Law Enforcement and Military operations that
is growing exponentially small. National adversaries are today in many
instances hybrid threats, that manifest criminal and military traits, these
often require deployment of hybrid-capability autonomous weapons imbued with
the capability to taken on both Military and/or Security objectives. The
Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of
Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that
required military response and police investigations against a fighting cell of
the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade
Planning UAV Activities for Efficient User Coverage in Disaster Areas
Climate changes brought about by global warming as well as man-made
environmental changes are often the cause of sever natural disasters. ICT,
which is itself responsible for global warming due to its high carbon
footprint, can play a role in alleviating the consequences of such hazards by
providing reliable, resilient means of communication during a disaster crisis.
In this paper, we explore the provision of wireless coverage through UAVs
(Unmanned Aerial Vehicles) to complement, or replace, the traditional
communication infrastructure. The use of UAVs is indeed crucial in emergency
scenarios, as they allow for the quick and easy deployment of micro and pico
cellular base stations where needed. We characterize the movements of UAVs and
define an optimization problem to determine the best UAV coverage that
maximizes the user throughput, while maintaining fairness across the different
parts of the geographical area that has been affected by the disaster. To
evaluate our strategy, we simulate a flooding in San Francisco and the car
traffic resulting from people seeking safety on higher ground
Multi-authored monograph
Unmanned aerial vehicles. Perspectives. Management. Power supply : Multi-authored monograph / V. V. Holovenskiy, T. F. Shmelova,Y. M. Shmelev and oth.; Science Editor DSc. (Engineering), T. F. Shmelova. – Warsaw, 2019. – 100 p. - ISBN 978-83-66216-10-5.У монографії аналізуються можливі варіанти енергопостачання та управління безпілотними літальними апаратами. Також розглядається питання прийняття рішення оператором безпілотного літального апарату при управлінні у надзвичайних ситуаціях. Рекомендується для фахівців, аспірантів і студентів за спеціальностями 141 - «Електроенергетика, електротехніка та електромеханіка», 173 - «Авіоніка» та інших суміжних спеціальностей.The monograph analyzes the possible options for energy supply and control of unmanned aerial vehicles. Also, the issue of decision-making by the operator of an unmanned aerial vehicle in the management of emergencies is considered.
Multi-criteria Evolution of Neural Network Topologies: Balancing Experience and Performance in Autonomous Systems
Majority of Artificial Neural Network (ANN) implementations in autonomous
systems use a fixed/user-prescribed network topology, leading to sub-optimal
performance and low portability. The existing neuro-evolution of augmenting
topology or NEAT paradigm offers a powerful alternative by allowing the network
topology and the connection weights to be simultaneously optimized through an
evolutionary process. However, most NEAT implementations allow the
consideration of only a single objective. There also persists the question of
how to tractably introduce topological diversification that mitigates
overfitting to training scenarios. To address these gaps, this paper develops a
multi-objective neuro-evolution algorithm. While adopting the basic elements of
NEAT, important modifications are made to the selection, speciation, and
mutation processes. With the backdrop of small-robot path-planning
applications, an experience-gain criterion is derived to encapsulate the amount
of diverse local environment encountered by the system. This criterion
facilitates the evolution of genes that support exploration, thereby seeking to
generalize from a smaller set of mission scenarios than possible with
performance maximization alone. The effectiveness of the single-objective
(optimizing performance) and the multi-objective (optimizing performance and
experience-gain) neuro-evolution approaches are evaluated on two different
small-robot cases, with ANNs obtained by the multi-objective optimization
observed to provide superior performance in unseen scenarios
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