Miniature Autonomous Underwater Vehicles are a major area of research and development today. Because of their size and agility, they are capable of exploring and operating in smaller bodies of water in addition to areas of the ocean that would be out of reach for a larger vehicle. Being autonomous requires that the system must be capable of performing without the need for human supervision, so use of external sensors such as sonar are needed to ensure the safety of the vehicle during missions. However, since all of the onboard instrumentation and external equipment must also be miniature in size, the implementation of a small sonar system is desirable. This thesis contains a brief introduction to sound and sonar, leading into a description of the design and development of a small, inexpensive sonar altimeter. Piezoelectric material is used for transduction in the sonar system while a PIC microcontroller processes the return signals from the water. This altimeter was made to be implemented on a miniature autonomous underwater vehicle developed by the Autonomous Systems and Controls Laboratory at Virginia Polytechnic Institute. In addition to being capable of reporting ocean depths, sonar systems can be used to aid in the navigation of underwater vehicles. A constant altitude controller based on sonar data has been designed, tested, and implemented on the autonomous underwater vehicle. Possibilities for an obstacle avoidance system involving sonar are also discussed in this thesis. / Master of Science

Presented in this thesis is a collision avoidance algorithm designed around an arc path model. The algorithm was designed for use on Virginia Tech robots entered in the 2003 and 2004 Intelligent Ground Vehicle Competition (IGVC) and on our 2004 entry into the DARPA Grand Challenge. The arc path model was used because of the simplicity of the calculations and because it can accurately represent the base kinematics for Ackerman or differentially steered vehicles. Clothoid curves have been used in the past to create smooth paths with continuously varying curvature, but clothoids are computationally intensive. The circular arc algorithm proposed here is designed with simplicity and versatility in mind. It is readily adaptable to ground vehicles of any size and shape. The algorithm is also designed to run with minimal tuning. The algorithm can be used as a stand alone reactive collision avoidance algorithm in simple scenarios, but it can be better optimized for speed and safety when guided by a global path planner. A complete navigation architecture is presented as an example of how obstacle avoidance can be incorporated in the algorithm. / Master of Science

The use of autonomous aerial vehicles (UAVs) to explore unknown environments is a growing field of research; of particular interest is locating a target that emits a signal within an unknown environment. Several physical processes produce scalar signals that attenuate with distance from their source, such as chemical, biological, electromagnetic, thermal, and radar signals. The natural decay of the signal with increasing distance enables a gradient ascent method to be used to navigate toward the target. The UAVs navigate around obstacles whose positions are initially unknown; a hybrid controller comprised of overlapping control modes enables robust obstacle avoidance in the presence of exogenous inputs by precluding topological obstructions. Limitations of a distributed gradient augmentation approach to obstacle avoidance are discussed, and an alternative algorithm is presented which retains the robustness of the hybrid control while leveraging local obstacle position information to improve non-collision reliability. A heterogeneous swarm of multirotors demonstrates the target locating problem, sharing information over a multicast wireless private network in a fully distributed manner to form an estimate of the signal's gradient, informing the direction of travel toward the target. The UAVs navigate around obstacles, showcasing both algorithms developed for obstacle avoidance. Each UAV performs its own target seeking and obstacle avoidance calculations in a distributed architecture, receiving position data from an OptiTrack motion capture system, illustrating the applicability of the control law to real world challenges (e.g., unsynchronized clocks among different UAVs, limited computational power, and communication latency). Experimental and theoretical results are compared. / Master of Science / In this project, a new method for locating a target using a swarm of unmanned drones in an unknown environment is developed and demonstrated. The drones measure a signal such as a beacon that is being emitted by the target of interest, sharing their measurement information with the other drones in the swarm. The magnitude of the signal increases as the drones move toward the target, allowing the drones to estimate the direction to the target by comparing their measurements with the measurements collected by other drones. While seeking the target in this manner, the drones detect obstacles that they need to avoid. An issue that arises in obstacle avoidance is that drones can get stuck in front of an obstacle if they are unable to decide which direction to travel; in this work, the decision process is managed by combining two control modes that correspond to the two direction options available, using a robust switching algorithm to select which mode to use for each obstacle. This work extends the approach used in literature to include multiple obstacles and allow obstacles to be detected dynamically, enabling the drones to navigate through an unknown environment as they locate the target. The algorithms are demonstrated on unmanned drones in the VT SpaceDrones test facility, illustrating the capabilities and effectiveness of the methods presented in a series of scenarios.

This dissertation aims to address how a change in landing substrate may change landing kinematics. To examine this possibility, mallards (Anas playtrhynchos) were used as a study species and 177 water landings were recorded through the use of two camera systems with photogrammetric capabilities. This enabled the landing trajectory and landing transition kinematics to be tracked in three dimensions. From the resulting position data three questions were pursued. Do mallards regulate landing kinematics through a ̇-constant strategy? With what kinematics do mallards land on water? Do landing kinematics respond to external factors, such as an obstacle to landing? Chapter 2 assesses the presence of a ̇-constant regulatory strategy and compares the implementation to other landing behaviors. Chapter 3 examines the variation observed in the landing kinematics of mallards, identifies the primary kinematic drivers of that variation, and detects differences in kinematic profile. Chapter 4 inspects the landing kinematics combined with the positions of all other waterfowl in the vicinity to test for the presence of obstacle avoidance behavior. / Doctor of Philosophy / Control of landing is an important ability for any flying animal. However, with the exception of perch landing, we know very little about how birds and other flyers land on a variety of different surfaces. Here, we aim to extend our knowledge in this area by focusing on how mallard ducks land on water. This dissertation addresses the following questions. Do mallards regulate landing speed and trajectory the same way as pigeons? At what speeds, angles, and postures do mallards land on water? Can mallards adjust landing behavior to avoid collisions with other birds on the water surface? Chapter 2 determines how mallards regulate landings and how it is similar and different from pigeons and several other flyers. Chapter 3 describes the speeds, angles, and postures used by mallards to land on water. In addition, this chapter finds evidence for at least two different categories of landing performed by mallards. Chapter 4 provides evidence that mallards avoid situations in which a collision with another bird is likely. However, it is unclear if this is an active choice made by the mallard or due to other circumstances related to the landing behavior. Overall, this dissertation illustrates how the landing behavior of mallards is similar to what has been documented in other animals. However there are significant differences such as higher impact speeds, and shallower angles. Both of which are likely related to the ability of water to absorb a greater amount of the impact forces than a perch or the ground would.

BACKGROUND:Community ambulation is a highly complex skill requiring the ability to adapt to increased environmental complexity and perform multiple tasks simultaneously. After stroke, individuals demonstrate a diminished ability to perform dual-tasks. Current evidence suggests that conventional rehabilitation does not adequately address gait-related dual-task impairments after stroke, which may be contributing to low levels of participation and physical inactivity in community-dwelling stroke survivors. The objective of this study is to investigate the efficacy of dual-task gait training in community-dwelling adults within 1 year of stroke. Specifically, we will compare the effects of dual-task gait training and single-task gait training on cognitive-motor interference during walking at preferred speed and at fastest comfortable speed (Aim 1), locomotor control during obstacle negotiation (Aim 2), and spontaneous physical activity (Aim 3).METHODS/DESIGN:This single-blind randomized controlled trial will involve 44 individuals within 12 months of stroke. Following baseline evaluation, participants will be randomly allocated to single- or dual-task gait training. Both groups will receive 12, 30-minute sessions provided one-on-one over 4-6 weeks in an outpatient therapy setting. Single-task gait training involves practice of gait activities incorporating motor relearning principles. Dual-task gait training involves an identical gait training protocol / the critical difference being that the dual-task gait training group will practice the gait activities while simultaneously performing a cognitive task for 75% of the repetitions. Blinded assessors will measure outcomes at baseline, post-intervention, and 6 months after completion of the intervention. The primary outcome measure will be dual-task effects on gait speed and cognition during unobstructed walking. Secondary outcomes include spatiotemporal and kinetic gait parameters during unobstructed single- and dual-task walking at preferred and fastest comfortable walking speeds, gait parameters during high and low obstacle crossing, spontaneous physical activity, executive function, lower extremity motor function, Timed Up and Go, balance self-efficacy, number of falls, and stroke-related disability. Hypotheses for each aim will be tested using an intention-to-treat analysis with repeated measures ANOVA design.DISCUSSION:This trial will provide evidence to help clinicians make decisions about the types of activities to include in rehabilitation to improve dual-task walking after stroke.TRIAL REGISTRATION:ClinicalTrials.gov NCT01568957

The purpose of this project is to implement obstacle avoidance algorithms to drive the articulated vehicle autonomously in an unknown environment, which is simulated by AgX Dynamics™ simulation software and controlled by Matlab® programming software. Three driving modes are developed for driving the vehicle (Manual, Semi-autonomous and Autonomous) in this project. Path tracking algorithms and obstacle avoidance algorithms are implemented to navigate the vehicle. A GUI was built and used for the manual driving mode in this project. The semi-autonomous mode checked different cases: change lanes, U-turn, following a line, following a path and figure 8 course. The autonomous mode is implemented to drive the articulated vehicle in an unknown environment with moving to a pose path tracking algorithm and VFH+ obstacle avoidance algorithm. Thus, the simulation model and VFH+ obstacle avoidance algorithm seems to be working fine and still can be improved for the autonomous vehicle. The result of this project showed a good performance of the simulation model. Moreover, this simulation software helps to minimize the cost of the articulated vehicle since all tests are in the simulation rather than in the reality.

Cada vez mais empilhadeiras robóticas são utilizadas para a tarefa de transporte em indústrias e armazéns. O gerenciamento dessas empilhadeiras é a chave para um sistema de transporte eficiente visando maximizar sua taxa de transferência. Um dos principais problemas na operação desses sistemas é a decisão de roteamento das empilhadeiras dentro dos depósitos. Este trabalho propõe um algoritmo de roteamento com a capacidade de realizar a otimização das rotas em tempo-real. Na computação da rota são considerados o desvio de obstáculos, as dimensões e as propriedades físicas das empilhadeiras, pois uma trajetória calculada deste ponto de referência está livre de colisões durante a execução do roteamento. Para realizar os testes foram utilizados os softwares Player/Stage, os quais permitem que simulações do funcionamento do sistema de roteamento sejam realizadas antes que os algoritmos sejam testados em robôs reais. Através dos testes simulados, analisou-se a capacidade de locomoção das empilhadeiras referente ao calculo da melhor rota no ambiente proposto, com o intuito de melhorar o ganho de performance no planejamento de trajetória. / Forklift robots have been increasingly used in transport tasks in industries and warehouses. The key to an efficient transport system is held by a sound management of these forklifts that aim to maximize the transference rate. One of the main problems faced by the transportation systems is routing decision for forklifts within warehouse. The present paper proposes a routing algorithm to calculate optimal routes in real time. Therefore, its computation takes into account obstacle avoidance, the dimension and physical properties of the forklifts, since the calculated path regarding the routing is conflict-free. Simulations were carried out using the software Player/Stage before the algorithms were tested in a real robot. Simulated tests were analyzed in order to observe the locomotion ability of forklifts regarding calculation of the best route in the environment proposed to improve the trajectory planning performance will be assessed.

Orientador: Lilian Teresa Bucken Gobbi / Banca: José Angelo Barela / Banca: Sérgio Teixeira Fonseca / Resumo: Durante a locomoção, ocorre um padrão de movimento visual referido como um campo de fluxo óptico. Para explorar como os ajustamentos locomotores são influenciados por este padrão, um paradigma experimental foi desenvolvido para anular o fluxo óptico durante a locomoção e ultrapassagem de obstáculo. O objetivo deste estudo foi investigar a contribuição de amostragens visuais estáticas e dinâmica na locomoção e ultrapassagem de obstáculos de diferentes alturas. Dez indivíduos (23,4 l 1,28 anos de idade, de ambos os gêneros) foram convidados a andar sobre uma passarela e ultrapassar um de dois obstáculos personalizados (obstáculo alto = altura do joelho e obstáculo baixo = altura do tornozelo) posicionado a 5m do ponto de partida. Diodos emissores de luz foram afixados no 5º metatarso e face lateral do calcâneo em ambos os pés e suas trajetórias foram filmados por quatro filmadoras digitais posicionadas bilateralmente à passarela. Dois blocos de tentativas foram apresentados em função das condições de amostragens visuais. No primeiro bloco, 10 tentativas com amostragem visual dinâmica (iluminação normal) foram apresentadas. No segundo bloco de tentativas, duas condições de amostragens visuais estáticas foram apresentadas de forma aleatória por meio de uma luz estroboscópica (2 flashes/segundo e 4 flashes/segundo). A duração de cada flash não ultrapassou 16ms e forneceu apenas imagens estáticas do ambiente. A altura do obstáculo foi randomizada em cada bloco de tentativas. Cinco tentativas para cada condição foram coletadas, totalizando 30 tentativas por participante. Todas as imagens foram digitalizadas e reconstruídas no plano tri-dimensional. As variáveis dependentes na fase de aproximação (comprimentos dos dois passos anteriores à ultrapassagem) e na fase de ultrapassagem... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: During locomotion, a pattern of visual motion referred as an optic flow field occurs. In order to explore how the locomotor adjustments are influenced by this pattern, an experimental paradigm was developed to remove the optic flow during locomotion and obstacle avoidance. The aim of this study was to investigate the contribution of the static and dynamic visual sampling on the locomotion and obstacle avoidance of different heights. Ten individuals (23.4 l 1.28 years of age, both genders) were invited to walk on a pathway and to avoid one out of two personalized obstacles (high obstacle = knee height and low obstacle = ankle height) positioned 5m from the starting position. Light emitting diodes were fixed on the fifth metatarsal and calcaneus lateral face in both feet and their trajectories were recorded by four digital cameras bilaterally positioned related to the pathway. Two trial blocks were presented depending of the visual sampling conditions. In the first block, 10 trials with visual dynamic sampling (normal light) were presented. In the second trial block, two conditions of the static visual sampling frequencies were presented in an randomized way by means of the stroboscopic light (2 flashes/second or 4 flashes/second). Each flash duration was about 16ms and provided only environmental static images. Obstacle height was randomized for each trial block. Five trials for each experimental condition were collected totalizing 30 trials for each participant. All images were digitalized and reconstructed in the 3D plane. Dependent variables in the approach phase (last two step lengths before crossing) and in the crossing phase (horizontal toe distance to the obstacle prior crossing, obstacle toe clearance and mean horizontal velocity for each foot) were selected. The results revealed differences... (Complete abstract, access undermentioned electronic address) / Mestre

The long white cane offers many benefits for the blind and visually impaired. Still, many report being injured both indoors and outdoors while using the long white cane. One frequent cause of injury is due to the fact that the long white cane cannot detect obstacles above the waist of the user. This thesis presents a system that attempts to augment the capabilities of the long white cane by sensing the environment around the user, creating a map of obstacles within the environment, and providing simple haptic feedback to the user. The proposed augmented cane system uses the Asus Xtion Pro Live infrared depth sensor to capture the user's environment as a point cloud. The open-source Point Cloud Library (PCL) and Robotic Operating System (ROS) are used to process the point cloud. The points representing the ground plane are extracted to more clearly define potential obstacles. The system determines the nearest point for each 1degree across the horizontal view. These nearest points are recorded as a ROS Laser Scan message and used in a simple haptic feedback system where the rumble feedback is based on two different cost functions. Twenty-two volunteers participated in a user demonstration that showed the augmented cane system can successfully communicate the presence of obstacles to blindfolded users. The users reported experiencing a sense of safety and confidence in the system's abilities. Obstacles above waist height are detected and communicated to the user. The system requires additional development before it could be considered a viable product for the visually impaired.

Using robots to navigate through un-mapped environments, specially man-made infrastructures, for the purpose of exploration or inspection is a topic that has gathered a lot of interest in the last years. Micro Aerial Vehicles (MAV's) have the mobility and agility to move quickly and access hard-to-reach areas where ground robots would fail, but using MAV's for that purpose comes with its own set of problems since any collision with the environment results in a crash. The control architecture used in a MAV for such a task needs to perform obstacle avoidance and on-line path-planning in an unknown environment with low computation times as to not lose stability. In this thesis a Non-linear Model Predictive Controller (NMPC) for obstacle avoidance and path-planning on an aerial platform will be established. Included are methods for constraining the available state-space, simulations of various obstacle avoidance scenarios for single and multiple MAVs and experimental validation of the proposed control architecture. The validity of the proposed approach is demonstrated through multiple experimental and simulation results. In these approaches, the positioning information of the obstacles and the MAV are provided by a motion-capture system. The thesis will conclude with the demonstration of an experimental validation of a centralized NMPC for collision avoidance of two MAV's.