Path planning and energy management of solar-powered unmanned ground vehicles

Many of the applications pertinent to unmanned vehicles, such as environmental research and analysis, communications, and information-surveillance and reconnaissance, benefit from prolonged vehicle operation time. Conventional efforts to increase the operational time of electric-powered unmanned vehicles have traditionally focused on the design of energy-efficient components and the identification of energy efficient search patterns, while little attention has been paid to the vehicle\u27s mission-level path plan and power management. This thesis explores the formulation and generation of integrated motion-plans and power-schedules for solar-panel equipped mobile robots operating under strict energy constraints, which cannot be effectively addressed through conventional motion planning algorithms. Transit problems are considered to design time-optimal paths using both Balkcom-Mason and Pseudo-Dubins curves. Additionally, a more complicated problem to generate mission plans for vehicles which must persistently travel between certain locations, similar to the traveling salesperson problem (TSP), is presented. A comparison between one of the common motion-planning algorithms and experimental results of the prescribed algorithms, made possible by use of a test environment and mobile robot designed and developed specifically for this research, are presented and discussed

Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

This research developed a method for multiple Unmanned Aircraft Systems (UAS) to efficiently collect data from a Wireless Sensor Networks (WSN). WSN are composed of any number of fixed, ground-based sensors that collect and upload local environmental data to over flying UAS. The three-step method first uniquely assigns aircraft to specific sensors on the ground. Second, an efficient flight path is calculated to minimize the aircraft flight time required to verify their assigned sensors. Finally, sensors reporting relatively higher rates of local environmental activity are re-assigned to dedicated aircraft tasked with concentrating on only those sensors. This work was sponsored by the Air Force Research Laboratory, Control Sciences branch, at Wright Patterson AFB. Based on simulated scenarios and preliminary flight tests, optimal flight paths resulted in a 14 to 32 reduction in flight time and distance when compared to traditional flight planning methods

Large space structures and systems in the space station era: A bibliography with indexes

Bibliographies and abstracts are listed for 1219 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1990 and December 31, 1990. The purpose is to provide helpful information to the researcher, manager, and designer in technology development and mission design according to system, interactive analysis and design, structural and thermal analysis and design, structural concepts and control systems, electronics, advanced materials, assembly concepts, propulsion, and solar power satellite systems

Path Planning and Communication Strategies to Enable Connectivity in Robotic Systems

There has been considerable interest in the area of communication-aware robotics in recent years, where the sensing, communication and motion objectives of robotic systems are jointly optimized. One particular open problem in this area is that of exploiting the mobility of unmanned vehicles in order to improve or satisfy communication objectives in realistic communication environments. Progress in this field could not only affect robust networked operation of unmanned vehicles but also would improve communication systems of the future (e.g. 5G), thus contributing to both areas of robotics and communications. This mobility-enabled connectivity and communication is the main area of interest in this dissertation.This dissertation is focused on path planning and communication strategies for robotic systems seeking to satisfy certain communication objectives in realistic communication environments experiencing path loss, shadowing and multipath fading. We consider realistic communication environments by leveraging and incorporating a probabilistic channel prediction framework that allows the robots to predict the channel quality at unvisited locations. This thesis then contributes to the area of mobility and connectivity through three main topics 1) energy-optimal distributed beamforming, 2) finding the statistics of the distance traveled until connectivity, and 3) path planning for connectivity. First, in energy-optimal distributed beamforming, we utilize the motion of a group of initially unconnected mobile robots to enable new forms of connectivity. More specifically, we co-optimize their locations and transmission powers to cooperatively enable connectivity through distributed beamforming. We further bring a foundational theoretical understanding to robotic distributed beamforming. Next, in finding the statistics of the distance traveled until connectivity, we analytically characterize the probability density function of the distance traveled by an initially unconnected robot until it gets connected to a remote node as it moves along a given path. We utilize tools from the stochastic differential equation literature to develop this characterization. Finally, in path planning for connectivity, we actively plan the path of a mobile robot such that it finds a connected spot with a minimum expected traveled distance (i.e., energy). The scenario considered in this part is in fact a more general one, and tackles the problem of path planning on a graph to minimize the expected cost incurred until the successful completion of a task. This framework has applications beyond path planning for connectivity, in areas such as celestial body imaging, human-robot collaboration, and search scenarios. We bring a foundational understanding to this problem. We show how this problem is inherently hard to solve (NP-complete) and also propose a path planner, based on a game-theoretic framework, that provides an asymptotic optimality guarantee.Overall, this thesis proposes novel strategies for utilizing the mobility of unmanned vehicles and enabling connectivity while considering the underlying energy constraints. We also provide a rigorous theoretical analysis of the aforementioned problems using a wide range of tools from communications theory, game theory, optimal control and time series literature. Moreover, through extensive realistic numerical studies using real channel parameters/data, we show the efficiency and performance of our proposed approaches

Mining and Managing Large-Scale Temporal Graphs

Large-scale temporal graphs are everywhere in our daily life. From online social networks, mobile networks, brain networks to computer systems, entities in these large complex systems communicate with each other, and their interactions evolve over time. Unlike traditional graphs, temporal graphs are dynamic: both topologies and attributes on nodes/edges may change over time. On the one hand, the dynamics have inspired new applications that rely on mining and managing temporal graphs. On the other hand, the dynamics also raise new technical challenges. First, it is difficult to discover or retrieve knowledge from complex temporal graph data. Second, because of the extra time dimension, we also face new scalability problems. To address these new challenges, we need to develop new methods that model temporal information in graphs so that we can deliver useful knowledge, new queries with temporal and structural constraints where users can obtain the desired knowledge, and new algorithms that are cost-effective for both mining and management tasks.In this dissertation, we discuss our recent works on mining and managing large-scale temporal graphs.First, we investigate two mining problems, including node ranking and link prediction problems. In these works, temporal graphs are applied to model the data generated from computer systems and online social networks. We formulate data mining tasks that extract knowledge from temporal graphs. The discovered knowledge can help domain experts identify critical alerts in system monitoring applications and recover the complete traces for information propagation in online social networks. To address computation efficiency problems, we leverage the unique properties in temporal graphs to simplify mining processes. The resulting mining algorithms scale well with large-scale temporal graphs with millions of nodes and billions of edges. By experimental studies over real-life and synthetic data, we confirm the effectiveness and efficiency of our algorithms.Second, we focus on temporal graph management problems. In these study, temporal graphs are used to model datacenter networks, mobile networks, and subscription relationships between stream queries and data sources. We formulate graph queries to retrieve knowledge that supports applications in cloud service placement, information routing in mobile networks, and query assignment in stream processing system. We investigate three types of queries, including subgraph matching, temporal reachability, and graph partitioning. By utilizing the relatively stable components in these temporal graphs, we develop flexible data management techniques to enable fast query processing and handle graph dynamics. We evaluate the soundness of the proposed techniques by both real and synthetic data. Through these study, we have learned valuable lessons. For temporal graph mining, temporal dimension may not necessarily increase computation complexity; instead, it may reduce computation complexity if temporal information can be wisely utilized. For temporal graph management, temporal graphs may include relatively stable components in real applications, which can help us develop flexible data management techniques that enable fast query processing and handle dynamic changes in temporal graphs

Large space structures and systems in the space station era: A bibliography with indexes (supplement 05)

Bibliographies and abstracts are listed for 1363 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1991 and July 31, 1992. Topics covered include technology development and mission design according to system, interactive analysis and design, structural and thermal analysis and design, structural concepts and control systems, electronics, advanced materials, assembly concepts, propulsion and solar power satellite systems

The Final Proceedings of the DOE/NASA Solar Power Satellite Program Review

The solar power satellite (SPS) concept defined as 'placing gigantic satellites in geosynchronous orbit to capture sunlight, changing the energy into an appropriate form for transmission to Earth, and introducing the energy into the electric power grid' is evaluated in terms of costs and benefits. The concept development and evaluation program is reviewed in four general areas: systems definition; environmental; societal; and comparative assessments. Specific factors addressed include: transportation, construction in space, methods of conversion of sunlight into energy, transmission to Earth, maintenance in orbit and decommissioning of satellites; environmental, political, and economic effects; and comparison of SPS to other forms of power generation, both terrestrial and in space