Ground effect refers to the apparent increase in lift that an aircraft experiences when it flies close to the ground. For helicopters, this effect has been modeled since the 1950's based on the work of Cheeseman and Bennett, perhaps the most common method for predicting hover performance due to ground effect. This model, however, is based on assumptions that do not hold for small-scale rotorcraft because it was developed specifically for conventional helicopters. It is not clear if the Cheeseman-Bennett model can be applied to today's multirotor UAVs. In this paper, we compare the Cheeseman-Bennett model to experimental results for rotor performance due to ground effect in several small-scale multirotor and single-rotor configurations. Experimental findings suggest that some of the conventional thinking surrounding helicopter ground effect cannot be applied directly to rotorcraft using fixed propellers at variable speeds (e.g. multirotors), and that it is necessary to adjust the helicopter models to better reflect the differences in such aircraft. The experimental results for multirotors presented are for multiple propeller configurations, speeds and spacings. Ultimately, this work will facilitate the development of an improved UAV flight controller that can accurately account for ground effect to improve flight stability near surfaces and structures.

This paper proposes a real-time system for pose estimation of an Unmanned Aerial Vehicle (UAV) using parallel image processing of a known marker. The system exploits the capabilities of a high-performance CPU/GPU embedded system in order to provide on-board high-frequency pose estimation, eliminating the need for transmitting the video stream off-board, and enabling autonomous takeoff and landing. The system is evaluated extensively with lab and field tests on board a small quadrotor. The results show that the proposed system is able to provide precise pose estimation with a framerate of at least 30 fps and an image resolution of 640×480 pixels. The use of the GPU for image filtering and marker detection provides an upper bound on the required computation time regardless of the complexity of the image thereby allowing for robust marker detection even in cluttered environments.

A semi-autonomous mobile self-leveling landing platform designed to launch, recover and re-launch VTOL UAVs without the need for human intervention is described. The landing platform is rugged, lightweight and inexpensive, making it ideal for civilian applications that require a base station from which a rotorcraft UAV can be launched and/or recovered on terrain that is normally unsuitable for UAV take-off and landing. This landing platform is capable of autonomously self-leveling on rough terrain and inclines up to 25°, and can operate in isolated remote locations for extended periods of time using large onboard lithium batteries and wireless communication. The unique design aspects of this landing platform are that it is mobile, self-leveling, and man-portable. A fully-operational prototype has been designed, constructed and evaluated. Design details and experimental results are presented to demonstrate the landing platform's functionality, and that all primary design requirements have been met.

In software testing, runtime code coverage is usually measured by instrumenting the executable code. In most cases the effect of the additional instructions is negligible, but for time-sensitive systems it can potentially alter the timing of executing code. This may lead to inconsistent test results, as the tests behave differently when run against non-instrumented code. In this paper, we discuss traditional code coverage techniques (i.e. instrumentation) and our code coverage technique called "iterative instrumentation" which has no runtime overhead. We analyze the impact of instrumentation runtime overhead through a case study of heuristic pathfinders. Next, we compare the effectiveness of iterative instrumentation to traditional instrumentation for measuring code coverage on a case study of control software. Finally, we discuss possible techniques to improve the quality of our technique including the limitations of this paper. Our studies confirm that instrumentation runtime overhead can alter the timing of time-sensitive software systems while our technique can be used effectively with no runtime overhead.

In this paper we present two new decentralized algorithms for autonomous intersection management and compare the performance of the algorithms with an established centralized solution. One of the algorithms addresses the problem through an unstructured peer-to-peer approach and the other uses a Distributed Hash Table to distribute knowledge of intersection usage among participating vehicles. We evaluate these algorithms through simulation and by comparing average delay to the performance of a centralized reservation-based algorithm. We find that in times of light congestion the decentralized algorithms perform as well as the centralized approach. During times of moderate or heavy congestion the unstructured peer-to-peer algorithm performs better than the centralized algorithm, and the DHT-based algorithm performs worse.

A limitation of small-scale, autonomous, vertical take-off and landing (VTOL) vehicles is their relatively short flight time. This hinders their broad applicability for many commercial applications. In previous work, we present the design and implementation of ISLANDS, an autonomous self-leveling landing platform for VTOL vehicles, along with an initial approach to their placement in the field of work. In this paper, we present several new approaches for improved station placement in a field of work of arbitrary shape and size, given sensor characteristics and the nature of the application. We present these algorithms in the context of a generic survey application, but they generalize to many other applications such as search and rescue, traffic monitoring, and environment monitoring.

The main goal of this paper is to describe a new methodology to evaluate the I/O responsiveness of microprocessors. This addresses the need for benchmarks for real-time systems that measure critical properties for system design that are not currently handled by traditional performance benchmarks. The benchmark developed under this methodology is tested on three microprocessor architectures: ARM, PIC and XMOS. The results of the benchmarks show that the response latency of systems can vary significantly between architectures and under different system loads.

In software testing, an oracle determines whether a test case passes or fails by comparing output from the program under test with the expected output. Since the identification of faults through testing requires that the bug is both exercised and the resulting failure is recognized, it follows that oracles are critical to the efficacy of the testing process. Despite this, there are few rigorous empirical studies of the impact of oracles on effectiveness. In this paper, we report the results of one such experiment in which we exercise seven core Java classes and two sample programs with branch-adequate, input only(i.e., no oracle) test suites and collect the failures observed by different oracles. For faults, we use synthetic bugs created by the muJava mutation testing tool. In this study we evaluate two oracles: (1) the implicit oracle (or "null oracle") provided by the runtime system, and (2) runtime assertions embedded in the implementation (by others) using the Java Modeling Language. The null oracle establishes a baseline measurement of the potential benefit of rigorous oracles, while the assertions represent a more rigorous approach that is sometimes used in practice. The results of our experiments are interesting. First, on a per-method basis, we observe that the null oracle catches less than 11% of the faults, leaving more than 89% uncaught. Second, we observe that the runtime assertions in our subjects are effective at catching about 53% of the faults not caught by null oracle. Finally, by analyzing the data using data mining techniques, we observe that simple, code-based metrics can be used to predict which methods are amenable to the use of assertion-based oracles with a high degree of accuracy.

Test adequacy criteria provide the engineer with guidance on how to populate test suites. While adequacy criteria have long been a focus of research, existing testing methods do not address many of the fundamental characteristics of distributed systems, such as distribution topology, communication failure, and timing. Furthermore, they do not provide the engineer with a means to evaluate the relative effectiveness of different criteria, nor the relative effectiveness of adequate test suites satisfying a given criterion. This paper makes three contributions to the development and use of test adequacy criteria for distributed systems: (1) a testing method based on discrete-event simulations; (2) a fault-based analysis technique for evaluating test suites and adequacy criteria; and (3) a series of case studies that validate the method and technique. The testing method uses a discrete-event simulation as an operational specification of a system, in which the behavioral effects of distribution are explicitly represented. Adequacy criteria and test cases are then defined in terms of this simulation-based specification. The fault-based analysis involves mutation of the simulation-based specification to provide a foil against which test suites and the criteria that formed them can be evaluated. Three distributed systems were used to validate the method and technique, including DNS, the domain name system.

Developers of distributed systems routinely construct discrete-event simulations to help understand and evaluate the behavior of inter-component protocols. Simulations are abstract models of systems and their environments, capturing basic algorithmic functionality at the same time as they focus attention on properties critical to distribution, including topology, timing, bandwidth, and overall scalability. We claim that simulations can be treated as a form of specification, and thereby used within a specification-based testing regime to provide developers with a rich new basis for defining and applying system-level test adequacy criteria. We describe a framework for evaluating distributed system test adequacy criteria, and demonstrate our approach on simulations and implementations of three distributed systems, including DNS, the Domain Name System.

Engineering distributed systems is a challenging activity. This is partly due to the intrinsic complexity of distributed systems, and partly due to the practical obstacles that developers face when evaluating and tuning their design and implementation decisions.This paper addresses the latter aspect, providing techniques for software engineers to automate the experimentation activity. Our approach is founded on a suite of models that characterize the distributed system under experimentation, the testbeds upon which the experiments are to be carried out, and the client behaviors that drive the experiments. The models are used by generative techniques to automate construction of the workloads,as well as construction of the scripts for deploying and executing the experiments on distributed testbeds. The framework is not targeted at a specific system or application model, but rather is a generic, programmable tool. We have validated our approach by performing experiments on a variety of distributed systems. For two of these systems, the experiments were deployed and executed on the PlanetLab wide-area testbed.Our experience shows that this framework can be readily applied to different kinds of distributed system architectures,and that using it for meaningful experimentation,especially in large-scale network environments, is advantageous.

This work proposes a routing scheme for content-based networking. A content-based network is a communication network that features a new advanced communication model where messages are not given explicit destination addresses, and where the destinations of a message are determined by matching the content of the message against selection predicates declared by nodes. Routing in a content-based network amounts to propagating predicates and the necessary topological information in order to maintain loop-free and possibly minimal forwarding paths for messages. The routing scheme we propose uses a combination of a traditional broadcast protocol and a content-based routing protocol. We present the combined scheme and its requirements over the broadcast protocol. We then detail the content-based routing protocol, highlighting a set of optimization heuristics. We also present the results of our evaluation, showing that this routing scheme is effective and scalable.