Underwater gliders are highly efficient, winged autonomous underwater vehicles that propel themselves by modifying their buoyancy and their center of mass. The center of mass is controlled by a set of servo-actuators which move one or more internal masses relative to the vehicle's frame. Underwater gliders are so efficient because they spend most of their time in stable, steady motion, expending control energy only when changing their equilibrium state. Motion control thus reduces to varying the parameters (buoyancy and center of mass) that affect the state of steady motion. These parameters are conventionally controlled through feedback, in response to measured errors in the state of motion, but one may also incorporate a feedforward component to speed convergence and improve performance. In this dissertation, first an approximate analytical expression for steady turning motion is derived by applying regular perturbation theory to a realistic vehicle model to develop a better understanding of underwater glider maneuverability, particularly with regard to turning motions. The analytical result, though approximate, is quite valuable because it gives better insight into the effect of parameters on vehicle motion and stability. Using these steady turn solutions, including the special case of wings level glides, one may construct feasible paths for the gliders to follow. Because the turning motion results are only approximate, however, and to compensate for model and environmental uncertainty, one must incorporate feedback to ensure convergent path following. This dissertation describes the development and numerical implementation of a feedforward/feedback motion control system intended to enhance locomotive efficiency by reducing the energy expended for guidance and control. It also presents analysis of the designed control system using slowly varying systems theory. The results provide (conservative) bounds on the rate at which the reference command (the desired state of motion) may be varied while still guaranteeing stability of the closed-loop system. Since the motion control system more effectively achieves and maintains steady motions, it is intrinsically efficient. The proposed control system enables speed, flight path angle, and turn rate, providing a mechanism for path following. The next step is to implement a guidance strategy, together with a path planning strategy, and one which continues to exploit the natural efficiency of this class of vehicle. The structure of the approximate solution for steady turning motion is such that, to first order in turn rate, the glider's horizontal component of motion matches that of "Dubins' car," a kinematic car with bounded turn rates. Dubins car is a classic example in the study of time-optimal control for mobile robots. For an underwater glider, one can relate time optimality to energy optimality. Specifically, for an underwater glider travelling at a constant speed and maximum flight efficiency (i.e., maximum lift-to-drag ratio), minimum time paths are minimum energy paths. Hence, energy-efficient paths can be obtained by generating sequences of steady wings-level and turning motions. These efficient paths can, in turn, be followed using the motion control system developed in this work. / Ph. D.

Assistive mobile robots, such as intelligent wheelchairs, that can navigate autonomously in response to high level commands from a user can greatly benefit people with cognitive and physical disabilities by increasing their mobility. In this work, we address the problem of safe, comfortable, and customizable motion planning of such assistive mobile robots. We recognize that for an assistive robot to be acceptable to human users, its motion should be safe and comfortable. Further, different users should be able to customize the motion according to their comfort. We formalize the notion of motion comfort as a discomfort measure that can be minimized to compute comfortable trajectories, and identify several properties that a trajectory must have for the motion to be comfortable. We develop a motion planning framework for planning safe, comfortable, and customizable trajectories in small-scale space. This framework removes the limitations of existing methods for planning motion of a wheeled mobile robot moving on a plane, none of which can compute trajectories with all the properties necessary for comfort. We formulate a discomfort cost functional as a weighted sum of total travel time, time integral of squared tangential jerk, and time integral of squared normal jerk. We then define the problem of safe and comfortable motion planning as that of minimizing this discomfort such that the trajectories satisfy boundary conditions on configuration and its higher derivatives, avoid obstacles, and satisfy constraints on curvature, speed, and acceleration. This description is transformed into a precise mathematical problem statement using a general nonlinear constrained optimization approach. The main idea is to formulate a well-posed infinite-dimensional optimization problem and use a conforming finite-element discretization to transform it into a finite-dimensional problem for a numerical solution. We also outline a method by which a user may customize the motion and present some guidelines for conducting human user studies to validate or refine the discomfort measure presented in this work. Results show that our framework is capable of reliably planning trajectories that have all the properties necessary for comfort. We believe that our work is an important first step in developing autonomous assistive robots that are acceptable to human users. / text

A simulação do movimento de humanos virtuais em mundos sintéticos é necessária a áreas tais como: jogos eletrônicos, filmes, ambientes virtuais colaborativos como Second Life R , simulação de pedestres, sistemas de treinamento e simulação de evacuações em situações de emergência. Contudo, mesmo sendo um importante tópico de pesquisa desde a década de 70, a simulação de comportamentos para personagens virtuais ainda é um desafio. O principal objetivo deste trabalho é estender a técnica proposta por Dapper et al. (DAPPER, 2007) onde foi apresentado um planejador de movimento para humanos virtuais que fornece trajetórias suaves e dependentes de parâmetros individuais dos agentes, permitindo a navegação de grupos de forma mais eficiente. Neste trabalho, é proposto um algoritmo para controlar o movimento de grupos em ambientes interativos e uma estratégia para manter a formação durante o deslocamento. O método é baseado em campos potenciais, ou seja, na solução numérica de problemas de valores de contorno envolvendo a equação de Laplace. O método proposto, é composto de duas camadas. Na primeira camada, um mapa para o controle do grupo é criado para possibilitar o controle de cada indivíduo, enquanto que na segunda camada, um algoritmo de planejamento de caminho é utilizado para o movimento do grupo como um todo. A técnica proposta combina o planejamento de movimento para grupos com a navegação baseada em esboços. Os resultados mostram que a técnica é robusta e pode ser utilizada em tempo-real. / The motion simulation of the movement of virtual humans in synthetic worlds is necessary for areas such as: electronic games, movies, collaborative virtual environments such as Second Life R , pedestrian simulation, training systems, simulation of evacuations in emergency situations. However, although being an important research topic since the 70s, the simulation of behaviors for virtual characters is still a challenge. Dapper et al. (DAPPER, 2007) developed a motion planner that provides smooth trajectories dependent on the individual parameters of the agents. The main goal of this work is to extend the technique proposed by Dapper, allowing for a more efficient control and navigation of groups. In this work, an algorithm for the control of group motion in interactive environments is proposed, along with a strategy for maintaining the group formation during the motion. The method is based on potential fields, more specifically, on the numeric solution of boundary-value problems involving the Laplace equation. The proposed method has two layers. In the first layer, a map for group control is created in order to allow for the control of every individual, while in the second layer a path planning algorithm is used for the movement of the group as a whole. The proposed technique combines the planning of group movements with a sketch-based navigation. The results show that the technique is robust and can be used in real-time.

A simulação do movimento de humanos virtuais em mundos sintéticos é necessária a áreas tais como: jogos eletrônicos, filmes, ambientes virtuais colaborativos como Second Life R , simulação de pedestres, sistemas de treinamento e simulação de evacuações em situações de emergência. Contudo, mesmo sendo um importante tópico de pesquisa desde a década de 70, a simulação de comportamentos para personagens virtuais ainda é um desafio. O principal objetivo deste trabalho é estender a técnica proposta por Dapper et al. (DAPPER, 2007) onde foi apresentado um planejador de movimento para humanos virtuais que fornece trajetórias suaves e dependentes de parâmetros individuais dos agentes, permitindo a navegação de grupos de forma mais eficiente. Neste trabalho, é proposto um algoritmo para controlar o movimento de grupos em ambientes interativos e uma estratégia para manter a formação durante o deslocamento. O método é baseado em campos potenciais, ou seja, na solução numérica de problemas de valores de contorno envolvendo a equação de Laplace. O método proposto, é composto de duas camadas. Na primeira camada, um mapa para o controle do grupo é criado para possibilitar o controle de cada indivíduo, enquanto que na segunda camada, um algoritmo de planejamento de caminho é utilizado para o movimento do grupo como um todo. A técnica proposta combina o planejamento de movimento para grupos com a navegação baseada em esboços. Os resultados mostram que a técnica é robusta e pode ser utilizada em tempo-real. / The motion simulation of the movement of virtual humans in synthetic worlds is necessary for areas such as: electronic games, movies, collaborative virtual environments such as Second Life R , pedestrian simulation, training systems, simulation of evacuations in emergency situations. However, although being an important research topic since the 70s, the simulation of behaviors for virtual characters is still a challenge. Dapper et al. (DAPPER, 2007) developed a motion planner that provides smooth trajectories dependent on the individual parameters of the agents. The main goal of this work is to extend the technique proposed by Dapper, allowing for a more efficient control and navigation of groups. In this work, an algorithm for the control of group motion in interactive environments is proposed, along with a strategy for maintaining the group formation during the motion. The method is based on potential fields, more specifically, on the numeric solution of boundary-value problems involving the Laplace equation. The proposed method has two layers. In the first layer, a map for group control is created in order to allow for the control of every individual, while in the second layer a path planning algorithm is used for the movement of the group as a whole. The proposed technique combines the planning of group movements with a sketch-based navigation. The results show that the technique is robust and can be used in real-time.

A simulação do movimento de humanos virtuais em mundos sintéticos é necessária a áreas tais como: jogos eletrônicos, filmes, ambientes virtuais colaborativos como Second Life R , simulação de pedestres, sistemas de treinamento e simulação de evacuações em situações de emergência. Contudo, mesmo sendo um importante tópico de pesquisa desde a década de 70, a simulação de comportamentos para personagens virtuais ainda é um desafio. O principal objetivo deste trabalho é estender a técnica proposta por Dapper et al. (DAPPER, 2007) onde foi apresentado um planejador de movimento para humanos virtuais que fornece trajetórias suaves e dependentes de parâmetros individuais dos agentes, permitindo a navegação de grupos de forma mais eficiente. Neste trabalho, é proposto um algoritmo para controlar o movimento de grupos em ambientes interativos e uma estratégia para manter a formação durante o deslocamento. O método é baseado em campos potenciais, ou seja, na solução numérica de problemas de valores de contorno envolvendo a equação de Laplace. O método proposto, é composto de duas camadas. Na primeira camada, um mapa para o controle do grupo é criado para possibilitar o controle de cada indivíduo, enquanto que na segunda camada, um algoritmo de planejamento de caminho é utilizado para o movimento do grupo como um todo. A técnica proposta combina o planejamento de movimento para grupos com a navegação baseada em esboços. Os resultados mostram que a técnica é robusta e pode ser utilizada em tempo-real. / The motion simulation of the movement of virtual humans in synthetic worlds is necessary for areas such as: electronic games, movies, collaborative virtual environments such as Second Life R , pedestrian simulation, training systems, simulation of evacuations in emergency situations. However, although being an important research topic since the 70s, the simulation of behaviors for virtual characters is still a challenge. Dapper et al. (DAPPER, 2007) developed a motion planner that provides smooth trajectories dependent on the individual parameters of the agents. The main goal of this work is to extend the technique proposed by Dapper, allowing for a more efficient control and navigation of groups. In this work, an algorithm for the control of group motion in interactive environments is proposed, along with a strategy for maintaining the group formation during the motion. The method is based on potential fields, more specifically, on the numeric solution of boundary-value problems involving the Laplace equation. The proposed method has two layers. In the first layer, a map for group control is created in order to allow for the control of every individual, while in the second layer a path planning algorithm is used for the movement of the group as a whole. The proposed technique combines the planning of group movements with a sketch-based navigation. The results show that the technique is robust and can be used in real-time.

Ce document explore l'utilisation de méthodes de planification automatique dans des simulations interactives. Lors de simulations de montage et de démontage de composants industriels en environnement virtuel, l'utilisateur peut nécessiter une assistance. Cette assistance est réalisée par l'utilisation d'une solution de planification de trajectoire en temps réel. Cette solution permet la construction interactive d'une chemin par la combinaison de l'avis de l'utilisateur avec la performance de planificateurs automatiques. / This PhD thesis explores the use of motion planning methods in interactive simulations. In the context of assembling and disassembling simulations of industrial components using haptic devices, the user may require assistance to find collision free paths. This assistance can be provided using real time interactive path planning methods. Our solution allows an interactive construction of free paths by combining the opinion of the user with the performance of fast modified automatic path planners.

<p>The problem with motorized wheelchairs is that they are large, clumsy and difficult to control. This is especially true if the driver has severely reduced capabilities. What we want is a wheelchair that can take instructionsfrom the driver and then based on its understanding of the environment, construct a plan that will take the user to the intended destination. The user should be able to sit in a room, tell the wheelchair that he wants to be in another room and the wheelchair should take him there as quickly and smoothly as possible. </p><p>The planner presented in this thesis uses a randomized bi-directional tree search. It builds two trees, one from the start state and one from the goal state by randomly sampling the control space of the robot. Each node is a state and each edge is a control input to the robot.</p><p>In order to decrease the execution time and improve path quality, the planner uses several heuristics to guide the planner. The heuristics are based on Rapidly-exploring Random Trees, Probabilistic Road-maps and the gradient method. </p><p>For a normal household situation, this planner can construct a decent plan in mere seconds on relatively slow hardware. Most times it finishes in a fraction of a second. </p><p>This means that the planner has the ability to run in real-time. As a consequence, the planner can handle a dynamic environment, inaccurate sensor readings and an inaccurate physical robot model.</p>

We consider the problem of moving a three dimensional solid object among polyhedral obstacles. The traditional formulation of configuration space for this problem uses three translational parameters and three angles (typically Euler angles), and the constraints between the object and obstacles involve transcendental functions. We show that a quaternion representation of rotation yields constraints which are purely algebraic in a higher-dimensional space. By simple manipulation, the constraints may be projected down into a six dimensional space with no increase in complexity. Using this formulation, we derive an efficient exact intersection test for an object which is translating and rotating among obstacles.

This report presents a system for generating a stable, feasible, and reachable grasp of a polyhedral object. A set of contact points on the object is found that can result in a stable grasp; a feasible grasp is found in which the robot contacts the object at those contact points; and a path is constructed from the initial configuration of the robot to the stable, feasible final grasp configuration. The algorithm described in the report is designed for the Salisbury hand mounted on a Puma 560 arm, but a similar approach could be used to develop grasping systems for other robots.

Mobile robots have found numerous applications in recent years, in areas such as consumer robotics, environmental monitoring, security and transportation. For information dissemination, multi-robot cooperation or operator intervention, reliable communications are important. The combination of communication constraints with other requirements in robotics, such as navigation and obstacle avoidance is called communication-aware motion planning. To facilitate integration, communication-aware methods should fit into traditional layered architectures of motion planning. This thesis contains two main contributions, applicable to such an architecture. The first contribution is to develop strategies for exploiting multipath fading while following a reference trajectory. By deviating from the reference, a robot can stop and communicate at positions with high signal strength, trading tracking performance for link quality. We formulate this problem in three different ways: First we maximize the link quality, subject to deterministic bounds on the tracking error. We control the velocity based on the position and channel quality. Second, we consider probabilistic tracking error bounds and develop a cascaded control architecture that performs time-triggered stopping while regulating the tracking error. Third, we formulate a hybrid optimal control problem, switching between standing still to communicate and driving to improve tracking. The resulting channel quality is analyzed and we perform extensive experiments to validate the communication model and compare the proposed methods to the nominal case of driving at constant velocity. The results show good agreement with the model and improvements of over 100% in the throughput when the channel quality is low. The second contribution is to plan velocities for a group of N robots, moving along pre-determined paths through an obstacle field. Robots can only communicate if they have an unobstructed line of sight, and the problem is to maintain connectivity while traversing the paths. This is mapped to motion planning in an N-dimensional configuration space. We propose and investigate two solutions, using a rapidly exploring random tree (RRT) and an exact method inspired by cell decomposition. The RRT method scales better with the problem size than the exact method, which has a worst-case time complexity that is exponential in the number of obstacles. But the randomization in the RRT method makes it difficult to set a timeout for the solver, which runs forever if a problem instance is unsolvable. The exact method, on the other hand, detects unsolvable problem instances in finite time. The thesis demonstrates, both in theory and experiments, that mobile robots can improve communications by planning trajectories that maintain visual connectivity, or by exploiting multipath fading when there is no line of sight. The proposed methods are well suited for integration in a layered motion planning architecture. / QC 20120117