Experimental Design of a Mobile Landing Platform to Assist Aerial Surveys in Fluvial Environments

194

The use of UAVs in areas ranging from agriculture over urban services to entertainment or simply as a hobby has rapidly grown over the last years. Regarding serious/commercial applications, UAVs have been considered in the literature, especially as mobile sensing/actuation platforms (i.e., as a delivery platform for an increasingly wide range of sensors and actuators). With regard to timely, cost-effective and very rich data acquisition, both, NEC Research as well as TNO are pursuing investigations into the use of UAVs and swarms of UAVs for scenarios where high-resolution requirements, prohibiting environments or tight time constraints render traditional approaches ineffective. In this review article, we provide a brief overview of safety and security-focused application areas that we identified as main targets for industrial and commercial projects, especially in the context of intelligent autonomous systems and autonomous/semi-autonomously operating swarms. We discuss a number of challenges related to the deployment of UAVs in general and to their deployment within the identified application areas in particular. As such, this article is meant to serve as a review and overview of the literature and the state-of-the-art, but also to offer an outlook over our possible (near-term) future work and the challenges that we will face there.

Section: Usage Of Uav Swarms In Smart Cities and For Public Safety Apmentioning

confidence: 99%

Review: Using Unmanned Aerial Vehicles (UAVs) as Mobile Sensing Platforms (MSPs) for Disaster Response, Civil Security and Public Safety

Hildmann

Kovács²

2019

194

“…They are increasingly considered as candidates for mobile/aerial urban sensing platforms [1]. Projected advances in cloud computing, wireless sensors and networked unmanned systems motivate this claim further, and indeed, in the literature UAVs are increasingly being suggested as flexible mobile platforms [2] used for applications as wide as general monitoring [3][4][5][6], monitoring and surveillance [7][8][9], to provide situational awareness support [10], detect victims or their life-signs [4] and participate in search and rescue (SAR) or aerial tracking [7]. This is especially applicable in the direct aftermath of a natural of man-made disaster as these events often result in partial or total loss of communication and data-collection infrastructure.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Voronoi Tessellation/Genetic Algorithm Approach for the Deployment of Drone-Based Nodes of a Self-Organizing Wireless Sensor Network (WSN) in Unknown and GPS Denied Environments

Eledlebi

Hildmann

Ruta

et al. 2020

Using autonomously operating mobile sensor nodes to form adaptive wireless sensor networks has great potential for monitoring applications in the real world. Especially in, e.g., disaster response scenarios—that is, when the environment is potentially unsafe and unknown—drones can offer fast access and provide crucial intelligence to rescue forces due the fact that they—unlike humans—are expendable and can operate in 3D space, often allowing them to ignore rubble and blocked passages. Among the practical issues faced are the optimizing of device–device communication, the deployment process and the limited power supply for the devices and the hardware they carry. To address these challenges a host of literature is available, proposing, e.g., the use of nature-inspired approaches. In this field, our own work (bio-inspired self-organizing network, BISON, which uses Voronoi tessellations) achieved promising results. In our previous approach the wireless sensors network (WSN) nodes were using knowledge about their coverage areas center of gravity, something which a drone would not automatically know. To address this, we augment BISON with a genetic algorithm (GA), which has the benefit of further improving network deployment time and overall coverage. Our evaluations show, unsurprisingly, an increase in energy cost. Two variations of our proposed GA-BISON deployment strategies are presented and compared, along with the impact of the GA. Counter-intuitively, performance and robustness increase in the presence of noise.

“…The objective of this multi-robot solution is to provide a collaboration system to perform data collection tasks from calm water environments in the frame of limnology studies. The selected aerial platform is based on the AR.Drone quadcopter while the surface vehicle, the Strider V1.0, a catamaran vessel, is a prototype platform developed specifically for this project [8] (see Figure 1). The aerial-maritime robot system is shown both in the real and in the simulated environment.…”

Section: Introductionmentioning

confidence: 99%

An Open Simulation Strategy for Rapid Control Design in Aerial and Maritime Drone Teams: A Comprehensive Tutorial

Velasco

Valente

Blanco

et al. 2020

Self Cite

The deployment of robot controllers into the real robotic platform is cumbersome and time consuming, especially when testing scenarios involve several robots or are sites not easily accessible. Besides this, most of the time, testing on the real platforms or real conditions provides little value in the early stages of controller design and prototype, phases where debugging and suitability of the controller are the main objectives. This paper proposes a simulation strategy for developing and testing controllers for Unmanned Aerial and Surface Vehicle coordination and interaction with the environment. The simulation strategy is based on V-REP and Matlab/Simulink which provide a large set of features, modularity and compatibility across platforms. Results show that this approach significantly reduces development and delivery times by providing an off-the-shelf simulation environment and a step-by-step implementation guidelines. The source code to deploy the simulations is available in an open-source repository.