Power-over-Tether UAS Leveraged for Nearly Indefinite Meteorological Data Acquisition In the Platte River Basin

The integration of unmanned aerial systems (UASs) has increased in the field of agriculture. These systems can provide data that was previously difficult to obtain to help increase efficiency and production. Typical commercial off the shelf (COTS) UASs have significant limitations in the form of small payloads, and short flight times which inhibit their ability to provide significant quantities of useful data. We present the development of a novel power-over-tether UAS that leverages the physical presence of the tether to integrate sensors at multiple altitudes along the tether. The UAS can acquire data nearly indefinitely to sense atmospheric conditions and gradients along the tether. We present the development of the prototyped system, along with the results of field experiments where we demonstrate 6 hours of continuous flight at 50 feet altitude, and a 1 hour flight at sunset to acquire atmospheric temperature from an array of sensors. An evaluation of the systems performance is presented along with a discussion of the systems future implications

Passive mobile robot localization within a fixed beacon field

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 67-70).This thesis describes a geometric algorithm for the localization of mobile nodes in networks of sensors and robots using bounded regions, in particular we explore the range-only and angle-only measurement cases. The algorithm is a minimalistic approach to localization and tracking when dead reckoning is too inaccurate to be useful. The only knowledge required about the mobile node is its maximum speed. Geometric regions are formed and grown to account for the motion of the mobile node. New measurements introduce new constraints which are propagated back in time to refine previous localization regions. The mobile robots are passive listeners while the sensor nodes actively broadcast making the algorithm scalable to many mobile nodes while maintaining the privacy of individual nodes. We prove that the localization regions found are optimal -- that is, they are the smallest regions which must contain the mobile node at that time. We prove that each new measurement requires quadratic time in the number of measurements to update the system, however, we demonstrate experimentally that this can be reduced to constant time. Numerous simulations are presented, as well as results from an underwater experiment conducted at the U.C. Berkeley R.B. Gump Biological Research Station on the island of Moorea, French Polynesia.by Carrick Detweiler.S.M

Flying by Fire: Making Controlled Burns Safer for Humans and UAVs

A temperature sensing circuit board was developed that will allow Nimbus Lab\u27s controlled burn starting UAV to react to the temperatures around it

Decentralized sensor placement and mobile localization on an underwater sensor network with depth adjustment capabilities

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 203-214).Over 70% of our planet is covered by water. It is widely believed that the underwater world holds ideas and resources that will fuel much of the next generation of science and business. Unfortunately, underwater operations are fraught with difficulty due to the absence of an easy way to collect and monitor data. In this thesis we propose a novel underwater sensor network designed to mitigate the problems of underwater sensing and communication. A key feature of this system is the ability of individual nodes to control their depth in water. This single degree of freedom allows the network to cooperatively optimize placement for communication and data collection while minimizing time and energy use. The sensor network also enables a GPS-like system for localizing underwater robots to aid in data retrieval and sensing. We develop a gradient-based decentralized controller that dynamically adjusts the depth of a network of underwater sensors to optimize sensing for modeling 3D properties of the water. We prove that the controller converges to a local minimum, and implement the controller on our underwater sensor network, where each node is capable of adjusting its depth. We verify the algorithm through simulations and in-water experiments. Most applications require that we associate a location with the sensed data. We have developed an underwater mobile robot localization algorithm that allows underwater robots to act as mobile sensors in the sensor network by using ranging information. The algorithm is a minimalist, geometric-based algorithm that only relies on knowing an upper bound on the robot speed and known static node locations. We prove that the algorithm finds the optimal location of the robot and analyze the algorithm in simulation and in water with our underwater sensor network.by Carrick Detweiler.Ph.D

Extending Wireless Rechargeable Sensor Network Life without Full Knowledge

When extending the life of Wireless Rechargeable Sensor Networks (WRSN), one challenge is charging networks as they grow larger. Overcoming this limitation will render a WRSN more practical and highly adaptable to growth in the real world. Most charging algorithms require a priori full knowledge of sensor nodes’ power levels in order to determine the nodes that require charging. In this work, we present a probabilistic algorithm that extends the life of scalable WRSN without a priori power knowledge and without full network exploration. We develop a probability bound on the power level of the sensor nodes and utilize this bound to make decisions while exploring a WRSN.We verify the algorithm by simulating a wireless power transfer unmanned aerial vehicle, and charging a WRSN to extend its life. Our results show that, without knowledge, our proposed algorithm extends the life of a WRSN on average 90% of what an optimal full knowledge algorithm can achieve. This means that the charging robot does not need to explore the whole network, which enables the scaling of WRSN. We analyze the impact of network parameters on our algorithm and show that it is insensitive to a large range of parameter values

CROP HEIGHT ESTIMATION WITH UNMANNED AERIAL VEHICLES

An unmanned aerial vehicle (UAV) can be configured for crop height estimation. In some examples, the UAV includes an aerial propulsion system, a laser scanner configured to face downwards while the UAV is in flight, and a control system. The laser scanner is configured to scan through a two - dimensional scan angle and is characterized by a maxi mum range. The control system causes the UAV to fly over an agricultural field and maintain, using the aerial propulsion system and the laser scanner, a distance between the UAV and a top of crops in the agricultural field to within a programmed range of distances based on the maximum range of the laser scanner. The control system determines, using range data from the laser scanner, a crop height from the top of the crops to the ground

Co-Regulated Consensus of Cyber-Physical Resources in Multi-Agent Unmanned Aircraft Systems

Intelligent utilization of resources and improved mission performance in an autonomous agent require consideration of cyber and physical resources. The allocation of these resources becomes more complex when the system expands from one agent to multiple agents, and the control shifts from centralized to decentralized. Consensus is a distributed algorithm that lets multiple agents agree on a shared value, but typically does not leverage mobility. We propose a coupled consensus control strategy that co-regulates computation, communication frequency, and connectivity of the agents to achieve faster convergence times at lower communication rates and computational costs. In this strategy, agents move towards a common location to increase connectivity. Simultaneously, the communication frequency is increased when the shared state error between an agent and its connected neighbors is high. When the shared state converges (i.e., consensus is reached), the agents withdraw to the initial positions and the communication frequency is decreased. Convergence properties of our algorithm are demonstrated under the proposed co-regulated control algorithm. We evaluated the proposed approach through a new set of cyber-physical, multi-agent metrics and demonstrated our approach in a simulation of unmanned aircraft systems measuring temperatures at multiple sites. The results demonstrate that, compared with fixed-rate and event-triggered consensus algorithms, our co-regulation scheme can achieve improved performance with fewer resources, while maintaining high reactivity to changes in the environment and system

Power-over-Tether UAS Leveraged for Nearly Indefinite Meteorological Data Acquisition In the Platte River Basin

The integration of unmanned aerial systems (UASs) has increased in the field of agriculture. These systems can provide data that was previously difficult to obtain to help increase efficiency and production. Typical commercial off the shelf (COTS) UASs have significant limitations in the form of small payloads, and short flight times which inhibit their ability to provide significant quantities of useful data. We present the development of a novel power-over-tether UAS that leverages the physical presence of the tether to integrate sensors at multiple altitudes along the tether. The UAS can acquire data nearly indefinitely to sense atmospheric conditions and gradients along the tether. We present the development of the prototyped system, along with the results of field experiments where we demonstrate 6 hours of continuous flight at 50 feet altitude, and a 1 hour flight at sunset to acquire atmospheric temperature from an array of sensors. An evaluation of the systems performance is presented along with a discussion of the systems future implications

Public Opinions of Unmanned Aerial Technologies in 2014 to 2019: A Technical and Descriptive Report

The primary purpose of this report is to provide a descriptive and technical summary of the results from similar surveys administered in fall 2014 (n = 576), 2015 (n = 301), 2016 (ns = 1946 and 2089), and 2018 (n = 1050) and summer 2019 (n = 1300). In order to explore a variety of factors that may impact public perceptions of unmanned aerial technologies (UATs), we conducted survey experiments over time. These experiments randomly varied the terminology (drone, aerial robot, unmanned aerial vehicle (UAV), unmanned aerial system (UAS)) used to describe the technology, the purposes of the technology (for economic, environmental, or security goals), the actors (public or private) using the technology, the technology’s autonomy (fully autonomous, partially autonomous, no autonomy), and the framing (promotion or prevention) used to describe the technology’s purpose. Initially, samples were recruited through Amazon’s Mechanical Turk, required to be Americans, and paid a small amount for participation. In 2016 we also examined a nationally representative samples recruited from Qualtrics panels. After 2016 we only used nationally representative samples from Qualtrics. Major findings are reported along with details regarding the research methods and analyses

Power-over-Tether UAS Leveraged for Nearly-Indefinite Meteorological Data Acquisition

Use of unmanned aerial systems (UASs) in agriculture has risen in the past decade. These systems are key to modernizing agriculture. UASs collect and elucidate data previously difficult to obtain and used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this paper, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS leveraging the physical presence of the tether to launch multiple sensors along the tether at multiple altitudes. With power from a ground station, the TAUS can acquire continuous data for several hours . The system is used to sense atmospheric conditions and temperature gradients across altitude. The development of the prototyped system is presented, along with the results of field experiments. The influence that power losses across the tether have on the sensors’ abilities to accurately sense is discussed. We demonstrate a 6-hour continuous flight at an altitude of 50 feet, and a 1-hour flight at sunset to acquire the gradually decreasing atmospheric temperature from an array of 6 sensors. An empirical evaluation of the system’s performance found that the prototype successively demonstrated proof of concept by considerably increasing flight times and throughput by simultaneously acquiring data from the sensor array. The TAUS will be improved by integrating performance-monitoring circuitry, elevated levels of algorithm-based autonomy, and multivariable sensors