Thesis (M.S.)--Linköping University, 2004. / Includes bibliographical references (p. 63-64). Also available online via the VTI web site (www.vti.se).

Durant ses activités quotidiennes, un marcheur interagit avec son environnement et en particulier avec les autres marcheurs, notamment en évitant toute collision. La nature de l'information visuelle utilisée pour une interaction sans collision est une question encore très ouverte à ce jour. Dans ce cadre, cette thèse vise à répondre aux questions suivantes : quels sont les indices visuels qu'un individu perçoit à partir du mouvement des autres ? Quels sont les mécanismes d'interprétation possibles et les modèles utilisés pour déterminer les possibles risques de collision ? Afin de répondre à ces questions, nous avons mis en place des expérimentations impliquant des évitements de collision entre deux marcheurs en utilisant la réalité virtuelle, permettant un contrôle détaillé de l'environnement visuel et des informations visuelles disponibles. La première étude s'est concentrée sur la nature de l'information visuelle fournie par un autre marcheur, en particulier, si ces informations sont extraites d’une perception locale considérant les segments corporels, ou d’une perception globale du mouvement du corps. La deuxième étude s'est concentrée sur l’influence de la trajectoire de l’autre marcheur (en ligne droite ou en courbe) sur la capacité à estimer de façon précise un possible risque de collision. Enfin, la troisième étude s'est concentrée sur l’effet du contact visuel sur l'interaction entre les deux marcheurs. Nous avons présenté ici le couplage entre les possibilités d'action perçues et les possibilités offertes par la nature de l'information visuelle et démontré que les marcheurs peuvent détecter les collisions futures prévues lorsqu'un autre marcheur suit une trajectoire avec des accélérations constantes. / During daily activities, a walker interacts with their environment, especially the other walkers, avoiding any collision with them. The nature of visual information that is used for a collision-free interaction requires further understanding. Specifically, the thesis aims to answer the following questions: what are the visual cues an individual perceives from the movement of others? What are the possible interpretation mechanisms and models used for determining future predicted crossing distances? To answer these questions, we designed experiments considering collision avoidance interactions between two walkers in virtual reality, allowing detailed control of the visual environment and the available visual information. The first study of the thesis focused on the nature of visual information provided from another walker, investigating whether these visual cues are extracted from local body parts or from global perception of the body motion. The second study investigated the influence of the walker's path (straight or curved), which the participant is interacting with for the accurate estimation of future risk of collision. Finally, the third study investigated whether eye contact influences the interaction. Here we have demonstrated the coupling of perceived actionopportunities affordances from the nature of visual information and evidenced that walkers can detect future predicted collisions when another walker follows a path with constant acceleration.

Road traffic safety has been a subject of worldwide concern. Dedicated short range communications (DSRC) is widely regarded as a promising enabling technology for collaborative safety applications (CSA), which can provide robust communication and affordable performance to build large scale CSA system. The main focus of this thesis is to develop solutions for DSRC QoS control in order to provide robust QoS support for CSA. The first design objective is to ensure robust and reliable message delivery services for safety applications from the DSRC networks. As the spectrum resources allocated to DSRC network are expected to be shared by both safety and non-safety applications, the second design objective is to make QoS control schemes bandwidth-efficient in order to leave as much as possible bandwidth for non-safety applications. The first part of the thesis investigates QoS control in infrastructure based DSRC networks, where roadside access points (AP) are available to control QoS control at road intersections. After analyse DSRC network capabilities on QoS provisioning without congestion control, we propose a two-phases adaptive QoS control method for DSRC vehicle networks. In the first phase an offline simulation based approach is used to and out the best possible system configurations (e.g. message rate and transmit power) with given numbers of vehicles and QoS requirements. It is noted that with different utility functions the values of optimal parameters proposed by the two phases centralized QoS control scheme will be different. The conclusions obtained with the proposed scheme are dependent on the chosen utility functions. But the proposed two phases centralized QoS control scheme is general and is applicable to different utility functions. In the second phase, these configurations are used online by roadside AP adaptively according to dynamic traffic loads. The second part of the thesis is focused on distributed QoS control for DSRC networks. A framework of collaborative QoS control is proposed, following which we utilize the local channel busy time as the indicator of network congestion and adaptively adjust safety message rate by a modified additive increase and multiplicative decrease (AIMD) method in a distributed way. Numerical results demonstrate the effectiveness of the proposed QoS control schemes.

Este trabalho propõe um sistema de manipulação robótica para interação física segura com objetos ou humanos em ambientes não estruturados. A proposta considera a execução de tarefas de manipulação e a prevenção e tratamento de colisões utilizando apenas uma lei de controle, o controle de impedância. A inovação científica consiste em um sistema multifuncional implementado com uma única lei de controle em contraste com os sistemas já existem que utilizam chaveamento entre controladores para cada diferente funcionalidade do sistema, e que apresentam diversas desvantagens como instabilidade e oscilações, aumento da complexidade de programação, entre outras. Inicialmente é proposto um planejador de manipulação e regrasping baseado na combinação de trajetórias suaves e na adaptação dos parâmetros de um controle de impedância em tempo de execução. A mudança da impedância para cada etapa é obtida pela modificação dos parâmetros de inércia, rigidez e amortecimento do controlador. A estabilidade desta mudança dinâmica é possível pela utilização de trajetórias suaves obtidas com planejador Squeezed Screw modificado, cujas trajetórias geradas são livres de descontinuidades na posição e na velocidade. Adicionalmente, a prevenção de colisões é realizada com o auxílio de campos potenciais de forças de repulsão formados pela análise de dados de um sistema de visão também proposto. Estes mesmos dados são utilizados para a construção de um mapa de impedâncias ao redor do objeto cuja finalidade é suavizar efeitos de colisões indesejadas. Experimentos com um robô de arquitetura aberta e com um sistema de visão de baixo custo foram realizados na execução tarefa de manipulação de referência para se avaliar o desempenho da metodologia proposta em diferentes condições de operação encontradas em ambientes não estruturados, como por exemplo: erros de medida de posição, de calibração, ocorrência de colisões, etc. A tarefa de manipulação eleita foi a reorientação em 60° de um objeto circular no plano. Os resultados obtidos nos experimentos mostram a capacidade do controle de impedância associado a trajetórias suaves de realizar a tarefa eleita segundo avaliação utilizando como métricas de desempenho a porcentagem de reorientação, que apresentou uma média de 80% mesmo na presença de erros de medida do sensor de visão e erros de determinação da posição do objeto. / Recent applications in various robotics areas consider interaction between robots and objects or humans in non-structured environments. Under these conditions, in addition to the desire of robots to be able to perform their main tasks, handling, navigation, rehabilitation, etc, it is also desired to prevent and properly handle possible unwanted collisions, whether with objects, with other robots, animals or humans. There are several proposed methods for avoidance, handling and reaction for collisions, however, a widely used strategy is the controller switching between different robot states. There are several drawbacks within this strategy: instability and oscillation, increased programming complexity and consequent increased failure risk, need for different sensors and consequent increase in cost, among others. This work proposes a system applied to the robotic manipulation which is based on only one control law, the impedance control, whose expected capacity is, further performing manipulation tasks, avoidance and handling of potential undesired collisions. It is initially proposed a manipulation planner based the combination of smooth trajectories and the adjustment of parameters an impedance control at runtime. The change of impedance for each phase is achieved by modifying the parameters: mass, spring and damping controller. The stability of this dynamic change is possible by using smooth trajectories obtained with a modified Squeezed Screw trajectory planner, whose paths are discontinuities free in the position and speed. Additionally, collision avoidance is achieved through potential fields the repulsive forces of formed by analysis of data vision. The same data is used to construct an impedance map surrounding the object which objective is collision handling. Experiments with an open architecture robot and a low cost vision system are carried out in the execution of a benchmark manipulation task to evaluate the proposal performance under different operating conditions found in unstructured environments, for example, position measurement errors, calibration problems, occurrence of collisions, among others.

Dû au grand intérêt porté à la simulation de foules, beaucoup d'algorithmes ont été et sont encore proposés. Toutefois, (1) il n'existe pas de méthode standard pour évaluer le réalisme et la flexibilité de ces algorithmes, et (2) même les algorithmes les plus récents produisent encore des artéfacts évidents. Abordant la première question, nous proposons une méthode visant à évaluer le réalisme des algorithmes de simulation de foules d'une manière objective et impartiale. ''Objective'' grâce à des métriques quantifiant la similitude entre les simulations et des données acquises en situation réelle. ''Impartiale'' grâce à l'estimation de paramètres permettant d'étalonner automatiquement les algorithmes en vue de décrire au mieux les données (par rapport aux métriques), permettant de comparer les algorithmes au mieux de leur capacité. Nous explorons aussi comment ce processus permet d'augmenter le niveau de contrôle d'un utilisateur sur la simulation tout en réduisant son implication. Abordant la deuxième question, nous proposons un nouvel algorithme d'évitement de collisions. Alors que les algorithmes existants prédisent les collisions en extrapolant linéairement les trajectoires des agents, nous allons au-delà grâce à une approche probabiliste et non-linéaire, prenant en compte entre autres la configuration de l'environnement, les trajectoires passées et les interactions avec les obstacles. Nous éliminons ainsi des simulations résultantes des artefacts tels que : les ralentissements et les agglomérats dérangeants d'agents, les mouvements oscillatoires non naturels, ou encore les manœuvres d'évitement exagérées/fausses/de dernière minute. Dans une troisième contribution, nous abordons aussi l'utilisation de notre travail sur l'évaluation et l'estimation de paramètres dans le cadre de systèmes plus larges. Dans un premier temps, nous l'appliquons à la simulation d'insectes, prenant en charge leur comportement local. Après avoir complété le système aux niveaux intermédiaire et global, cette approche basée-données est capable de simuler correctement des essaims d'insectes. Dans un second temps, nous appliquons notre travail au suivi de piétons, construisant un ''méta-algorithme'' servant à calculer la probabilité de transition d'un filtre particulaire, et surpassant les systèmes existants. / With the considerable attention crowd simulation has received, many algorithms have been and are being proposed. Yet, (1) there exists no standard scheme to evaluate the accuracy and flexibility of these algorithms, and (2) even the most recent algorithms produce noticeable simulation artifacts. Addressing the first issue, we propose a framework aiming to provide an objective and fair evaluation of the realism of crowd simulation algorithms. ''Objective'' here means the use of various metrics quantifying the similarity between simulations and ground-truth data acquired with real pedestrians. ''Fair'' here means the use of parameter estimation to automatically tune the tested algorithms to match the ground-truth data as closely as possible (with respect to the metrics), effectively allowing to compare algorithms at the best of their capability. We also explore how this process can increase a user's control on the simulation while reducing the amount of necessary intervention. Addressing the second issue, we propose a new collision-avoidance algorithm. Where current algorithms predict collisions by linearly extrapolating agents' trajectories, we better predict agents' future motions in a probabilistic, non-linear way, taking into account environment layout, agent's past trajectories and interactions with other obstacles among other cues. Resulting simulations do away with common artifacts such as: slowdowns and visually erroneous agent agglutinations, unnatural oscillation motions, or exaggerated/last-minute/false-positive avoidance manoeuvres. In a third contribution, we also explore how evaluation and parameter estimation can be used as part of wider systems. First, we apply it to insect simulation, taking care of local insect behavior. After completing it at the intermediate and global levels, the resulting data-driven system is able to correctly simulate insect swarms. Second, we apply our work to pedestrian tracking, constructing a ''meta-algorithm'', more accurately computing motion priors for a particle-filter-based tracker, outperforming existing systems.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-16T17:29:20Z No. of bitstreams: 1 alexandremenezesteixeira.pdf: 8409444 bytes, checksum: df76f8cbe4e829db629062da1fd25bc7 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2015-12-17T11:07:03Z (GMT) No. of bitstreams: 1 alexandremenezesteixeira.pdf: 8409444 bytes, checksum: df76f8cbe4e829db629062da1fd25bc7 (MD5) / Made available in DSpace on 2015-12-17T11:07:03Z (GMT). No. of bitstreams: 1 alexandremenezesteixeira.pdf: 8409444 bytes, checksum: df76f8cbe4e829db629062da1fd25bc7 (MD5) Previous issue date: 2015-02-23 / FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais / Monitorar um ambiente através de múltiplos robôs autônomos em um espaço compartilhado sem que haja colisões é um grande desafio nos dias atuais. Várias pesquisas na área de robótica tem sido feitas para desenvolver essa tarefa. Sendo assim, este trabalho atua na coordenação de movimento de múltiplos robôs de serviço percorrendo de forma cíclica caminhos que se interceptam. É desejável que os robôs sigam pelos caminhos inicialmente planejados sem mudá-los durante a missão. Para evitar possíveis colisões, um controlador central foi desenvolvido para planejar as velocidades médias que os robôs deverão efetuar em cada trecho do circuito, maximizando o menor intervalo de tempo t que eles cruzam por um mesmo ponto de colisão. A solução centralizada utilizada neste trabalho foi modelada como um problema Mixed Interger Linear Programming (MILP) sendo usado o software Linear Interactive and General Optimizer (LINGO) para maximizar t e encontrar para cada robô os tempos de percurso para cada parte do caminho. Foi desenvolvida uma aplicação em C++ capaz de iniciar o processo de otimização e receber os tempos otimizados de percurso de cada robô, usados para determinar as suas respectivas velocidades médias. Além disso, esta rotina de programação teve como objetivo realizar o controle dos robôs, navegando-os com o auxílio do framework Robot Operating System (ROS) integrado ao LINGO. Para localizá-los no espaço utilizou-se um pacote de visão computacional do ROS denominado ARPOSE, com o intuito de descobrir suas respectivas posições e orientações em relação à um eixo de referência global. Por fim, simulações e testes reais foram realizados sobre um grupo de robôs para demonstrar a eficácia da abordagem. Os resultados obtidos foram satisfatórios, o que possibilitou atingir os objetivos propostos. / Monitoring an environment using multi-autonomous robots operating in a shared workspace without collisions with each other is a great challenge nowadays. Many researchs have been done to develop this important task in robotics. Thus, this thesis deals with coordinating the motions of multiple working robots traversing periodic intersecting paths. It is desired that mobile robots following the initially designed paths without change them during the mission. To avoid any collision a centralized controller was developed to planner the velocity profile of the robots over the predefined paths, maximizing the smallest time margin t that the robots cross over a same collision point. The centralized solution used in this work was modeled as a Mixed Integer Linear Programming (MILP) problem using the Linear Interactive and General Optimizer (LINGO) software to maximize t and to find for each robot the sub-path traversal time. It was developed a C++ code capable to start the optimization process and receive for each robot the optimized traversal times, used to calculate their respectives average speeds. Besides, this code was used to control the robots, which was done through the Robot Operating System (ROS) framework integrated with LINGO. A computer vision ROS package named ARPOSE was used to localize the robots during the task, calculating their poses relative the global reference frame. Finally, to demonstrate the effectiveness of the approach, simulantions and real tests was performed on mobile robots group. The results obtained were satisfactory, which allowed to achieve the goals.

This thesis explain today and future technologies of air traffic collision avoidance systems and of its utilizability by unmanned aircraft. The first part describes the UAVs and their categorization. Next part deals with the legislative requirements for their operation. The main part deals with TCAS, ADS-B, FLARM and others that are now used in civil aviation as a key technology to avoid a collision. The last part describes the UAV systems with a focus on the actual sensors used in systems for unmanned aerial vehicles for collision avoidance. The whole work deals with issues of development of collision avoidance systems and summarizes the current technology with a view to its possible application in the near future.

The thesis aims to design and implement an Android application with ability to control the autopilot of the Skydog aircraft model using the wireless telemetry. The application shall receive data from an aircraft model gathered from various installed sensors. These data shall be then processed and corresponding instructions for autopilot shall be sent back. When collision with terrain or obstacle is detected, the application shall send instructions to autopilot to avoid such collision. RRT algorithm is used to find collision-free flight trajectory. Database of known obstacles and digital terrain model are provided to application in formats XML and GeoTIFF respectively.

This compilation thesis presents an overarching framework on the utilization of nonlinear model predictive control(NMPC) for various applications in the context of Unmanned Aerial Vehicle (UAV) path planning and collision avoidance. Fast and novel optimization algorithms allow for NMPC formulations with high runtime requirement, as those posed by controlling UAVs, to also have sufficiently large prediction horizons as to in an efficient manner integrate collision avoidance in the form of set-exclusion constraints that constrain the available position-space of the robot. This allows for an elegant merging of set-point reference tracking with the collision avoidance problem, all integrated in the control layer of the UAV. The works included in this thesis presents the UAV modeling, cost functions, constraint definitions, as well as the utilized optimization framework. Additional contributions include the use case on multi-agent systems, how to classify and predict trajectories of moving (dynamic) obstacles, as well as obstacle prioritization when an aerial agent is in the precense of more obstacles, or other aerial agents, than can reasonably be defined in the NMPC formulation. For the cases of dynamic obstacles and for multi-agent distributed collision avoidance this thesis offers extensive experimental validation of the overall NMPC framework. These works push the limits of the State-of-the-Art regarding real-time real-life implementations of NMPC-based collision avoidance. The works also include a novel RRT-based exploration framework that combines path planning with exploration behavior. Here, a multi-path RRT * planner plans paths to multiple pseudo-random goals based on a sensor model and evaluates them based on the potential information gain, distance travelled, and the optimimal actuation along the paths.The actuation is solved for as as the solutions to a NMPC problem, implying that the nonlinear actuator-based and dynamically constrained UAV model is considered as part of the combined exploration plus path planning problem. To the authors best knowledge, this is the first time the optimal actuation has been considered in such a planning problem. For all of these applications, the utilized optimization framework is the Optimization Engine: a code-generation framework that generates a custom Rust-based solver from a specified model, cost function, and constraints. The Optimization Engine solves general nonlinear and nonconvex optimization problems, and in this thesis we offer extensive experimental validation of the utilized Proximal-Averaged Newton-type method for Optimal Control (PANOC) algorithm as well as both the integrated Penalty Method and Augmented Lagrangian Method for handling the nonlinear nonconvex constraints that result from collision avoidance problems.

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