Second-Order Coverage Control for Multi-Agent UAV Photogrammetry

Unmanned Aerial Vehicles equipped with cameras can be used to automate image capture for generating 3D models via photogrammetry. Current methods rely on a single vehicle to capture images sequentially, or use pre-planned and heuristic imaging configurations. We seek to provide a multi-agent control approach to capturing the images required to 3D map a region. A photogrammetry cost function is formulated that captures the importance of sharing feature-dense areas across multiple images for successful photogrammetry reconstruction. A distributed second-order coverage controller is used to minimise this cost and move agents to an imaging configuration. This approach prioritises high quality images that are simultaneously captured, leading to efficient and scalable 3D mapping of a region. We demonstrate our approach with a hardware experiment, generating and comparing 3D reconstructions from image sets captured using our approach to those captured using traditional methods.Comment: 8 pages, 4 figure

Asynchronous Event-Triggered Control for Non-Linear Systems

With the increasing ubiquity of networked control systems, various strategies for sampling constituent subsystems' outputs have emerged. In contrast with periodic sampling, event-triggered control provides a way to efficiently sample a subsystem and conserve network resource usage, by triggering an update only when a state-dependent error threshold is satisfied. Herein we describe a scheme for asynchronous event-triggered control (ETC) of a nonlinear plant using sampler subsystems with hybrid dynamics. By exploiting inherent differences in the plant and controllers time scales, the proposed scheme permits independent sampling of plant and controller states. We extend existing ETC literature by adopting a more general representation of the sampler subsystem dynamics, thus accommodating different sampling schemes for both synchronous and asynchronous ETC applications. We present a numerical example in order to illustrate important operational considerations for the proposed scheme

UAV flocking with wind gusts: adaptive topology and model reduction

Abstract-In this paper, we examine the problem of UAV flocking in the presence of wind gusts. Firstly, we model a velocity consensus-based leader-follower system exposed to gust disturbances and design an optimal controller, in the linear quadratic sense, to improve velocity tracking. We then proceed to examine topological features that promote the performance of such optimal controllers to design a network rewiring protocol for improved system performance. Finally we present a novel partitioning schemed, dubbed leader partition, in order to fuse "similar" states in the network, forming a graph theoretic method for model reduction

Distributed Online Topology Design for Network-level Disturbance Rejection

Abstract-In this paper, we examine a networked multiagent system running the consensus protocol susceptible to misinformation from its environment. The influenced dynamics are modeled with leader-follower dynamics and the impact of the foreign input is measured through the open loop H2 norm of the network dynamics. To dampen the external disturbances a novel decentralized edge reweighting method is proposed. The method is composed of a decentralized conjugate gradient method coupled with a decentralized online optimization algorithm. The uncertainties of the effect of local rewiring and unknown environmental influences are demonstrated to be well-suited to the online regret framework. A simulation of the reweighting method is discussed and shown to have a small regret

Robust placement and sizing of charging stations from a novel graph theoretic perspective

This paper proposes analytical approaches to extend the capacity of existing networks of electric vehicles (EVs) by placement of additional charging stations (CSs) as well as determining the sizes of existing and new CSs in order to handle future expansions of EVs. The EV flow at CSs is modeled by a graph where nodes are potential locations for CSs and edges are uncertain parameters representing the variable EV flow at CSs. The required extra CS locations are explored by transforming the CS placement problem into a controllability framework addressed by maximum matching principle (MMP). To find the sizes of each CS, the graph of CS network is partitioned featuring only one CS in each subgraph. The size of CS in each subgraph is then determined by transforming the problem into the problem of robust stability of a system with uncertain parameters where each parameter is associated with an edge of subgraph. The zero exclusion principle is then tested for the related Kharitonov rectangles and polygonal polynomials of closed loop system with selected feedback gain as CS capacity. The proposed analytical approach is tested on the existing Tesla CS Network of Sydney. The locations of extra required CSs as well as the sizes of existing and new CSs are determined to maintain the waiting times at all stations below the threshold level

A graph automorphic approach for placement and sizing of charging stations in EV network considering traffic

This paper proposes a novel graph-based approach with automorphic grouping for the modelling, synthesis, and analysis of electric vehicle (EV) networks with charging stations (CSs) that considers the impacts of traffic. The EV charge demands are modeled by a graph where nodes are positioned at potential locations for CSs, and edges represent traffic flow between the nodes. A synchronization protocol is assumed for the network where the system states correspond to the waiting time at each node. These models are then utilized for the placement and sizing of CSs in order to limit vehicle waiting times at all stations below a desirable threshold level. The main idea is to reformulate the CS placement and sizing problems in a control framework. Moreover, a strategy for the deployment of portable charging stations (PCSs) in selected areas is introduced to further improve the quality of solutions by reducing the overshooting of waiting times during peak traffic hours. Further, the inherent symmetry of the graph, described by graph automorphisms, are leveraged to investigate the number and positions of CSs. Detailed simulations are performed for the EV network of Perth Metropolitan in Western Australia to verify the effectiveness of the proposed approach

Exotic states in a simple network of nanoelectromechanical oscillators.

Synchronization of oscillators, a phenomenon found in a wide variety of natural and engineered systems, is typically understood through a reduction to a first-order phase model with simplified dynamics. Here, by exploiting the precision and flexibility of nanoelectromechanical systems, we examined the dynamics of a ring of quasi-sinusoidal oscillators at and beyond first order. Beyond first order, we found exotic states of synchronization with highly complex dynamics, including weak chimeras, decoupled states, traveling waves, and inhomogeneous synchronized states. Through theory and experiment, we show that these exotic states rely on complex interactions emerging out of networks with simple linear nearest-neighbor coupling. This work provides insight into the dynamical richness of complex systems with weak nonlinearities and local interactions