UAV missions often require specific geometric con-straints to be satisfied between ground locations and the vehicle location. Such requirements are typical for contexts where line-of-sight must be maintained between t...
UAV missions often require specific geometric con-straints to be satisfied between ground locations and the vehicle location. Such requirements are typical for contexts where line-of-sight must be maintained between the vehicle location and the ground control location and are also important in surveillance applications where the UAV wishes to be able to sense, e.g., with a camera sensor, a specific region within a complex geometric environment. This problem is further complicated when the ground location is generalized to a convex 2D polygonal region. This article describes the theory and implementation of a system which can quickly calculate the 3D volume that encloses all 3D coordinates from which a 2D convex planar region can be entirely viewed; referred to as a visibility volume. The proposed approach computes visibility volumes using a combination of depth map computation using GPU-acceleration and geometric boolean operations. Solutions to this problem require complex 3D geometric analysis techniques that must execute using arbitrary precision arithmetic on a collection of discontinuous and non-analytic surfaces. Post-processing steps incorporate navigational constraints to further restrict the enclosed coordinates to include both visibility and navigation constraints. Integration of sensing visibility constraints with navigational constraints yields a range of navigable space where a vehicle will satisfy both perceptual sensing and navigational needs of the mission. This algorithm then provides a synergistic perception and navigation sensitive solution yielding a volume of coordinates in 3D that satisfy both the mission path and sensing needs.
Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human's longest and strongest bone - the femur - as an example, it is consist of two characte...
We propose a scalable, hierarchical qubit mapping and routing algorithm that harnesses the power of circuit synthesis. First, we decompose large circuits into subcircuits small enough to be directly resynthesized. For...
We propose a scalable, hierarchical qubit mapping and routing algorithm that harnesses the power of circuit synthesis. First, we decompose large circuits into subcircuits small enough to be directly resynthesized. For each block, we pre-synthesize them for all permutations of its input and output qubits. Following this offline step, we employ a permutation-aware, block-based generalization of the popular SABRE mapping algorithm. This mapping step stitches together blocks by choosing an input-output permutation that minimizes intrablock gate count and required inter-block communication (SWAP and bridge gates). Our approach has a twofold advantage: 1) circuit synthesis may eliminate more two-qubit gates than other optimizing compilers; 2) considering all permutations of input and output qubits eliminates communication operations transparently. In contrast, other mapping algorithms can only introduce communication operations. We show that we can produce better-quality circuits than commercial compilers: shorter by up to 68% (18% on average) fewer gates than Qiskit, up to 36% (9% on average) fewer gates than Tket. We outperform BQSkit, a permutation-unaware, synthesis-based compiler, by up to 67% (21% on average) fewer gates. We also exceed experimental optimal mappers such as OLSQ in quality (10.7% shorter circuits) and time to solution. Our scalable, heuristic approach can be seamlessly integrated into any quantum circuit compiler or optimization infrastructure, and it applies well to any qubit technology, such as superconducting and trapped ions.
We show that if a ternary quartic form is convex, then it must be sos-convex;i.e, if the Hessian H(x) of a ternary quartic form is positive semidefinite for all x, then the biquadratic form yT H(x)y in the variables x...
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The way we travel is changing rapidly, and Cooperative Intelligent Transportation systems (C-ITSs) are at the forefront of this evolution. However, the adoption of C-ITSs introduces new risks and challenges, making cy...
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Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the ...
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ISBN:
(数字)9798350377644
ISBN:
(纸本)9798350377651
Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay.
Adjoint shape optimization method is implemented to design SOI-based power splitters with arbitrary ratios. Splitters with ratios of 1:2, 1:4 and 1:8 are demonstrated with loss below 0.28 dB over a bandwidth of 100 nm...
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Inspired by the fiber-optic extrinsic Fabry-Perot interferometer, we report a novel and universal ultra-sensitive microwave Fabry-Perot sensing platform based on an open-ended hollow coaxial cable resonator (OE-HCCR) ...
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Adjoint shape optimization method is implemented to design SOI-based power splitters with arbitrary ratios. Splitters with ratios of 1:2, 1:4 and 1:8 are demonstrated with loss below 0.28 dB over a bandwidth of 100 nm...
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