Designing an algorithm for bioloid humanoid navigating in its indoor environment

Gait analyses are the preliminary requirements to establish a navigation system of a humanoid robot. Designing a suitable indoor environment and its mapping are also important for the android localization, selection of a goal to achieve it and to perform the assigned tasks in its surroundings. This paper delineates the various gaits like walking, turning, obstacle overcoming and step up-down stairs for a humanoid system. The writing also explicates the design of the indoor test environment with the stationary obstacles placed on the navigation routes. The development of an efficient algorithm is also excogitated based on the various analyses of gaits and the predefined map of the test environment. As the navigation map is predetermined, the designed algorithm animates the humanoid to navigate by selecting an optimal route, depending on some external commands, to reach at the goal position. Finally the performance of the system is analysed based on the elapsed time of the navigation action with the validation of optimal navigation strategy where the designed algorithm demonstrates the robustness of its implementation and execution

Dynamic Balance and Gait Metrics for Robotic Bipeds

For legged robots to be useful in the real world, they must be able to balance and walk reliably. Both of these abilities improve when a system is more effective at moving itself around relative to its contacts (i.e., its feet). Achieving this type of movement depends both on the controller used to perform the motion and the physical properties of the system. Although much work has been done on the development of dynamic controllers for balance and gait, only limited research exists on how to quantify a system’s physical balance capabilities or how to modify the system to improve those capabilities. From the control perspective, there are three strategies for maintaining balance in bipeds: flexing, leaning, and stepping. Both stepping and leaning strategies typically depend on balance points (critical points used for maintaining or regaining balance) to determine whether or not a step is needed, and if so, where to step. Although several balance point estimators exist, the majority of these methods make undesirable assumptions (e.g., ignoring the impact dynamics, assuming massless legs, planar motion, etc.). From the physical design perspective, one promising approach for analyzing system performance is a set of dynamic ratios called velocity and momentum gains, which are dependent only on the (scale-invariant) dynamic parameters and instantaneous configuration of a system, enabling entire classes of mechanisms to be analyzed at the same time. This thesis makes four key contributions towards improving biped balancing capabilities. First, a dynamic bipedal controller is proposed which uses a 3D balance point estimator both to respond to disturbances and produce reliable stepping. Second, a novel balance point estimator is proposed that facilitates stepping while combining and expanding the features of existing 2D and 3D estimators to produce a generalized 3D formulation. Third, the momentum gain formulation is extended to general 2D and 3D systems, then both gains are compared to centroidal momentum via a spatial formulation and incorporated into a generalized gain definition. Finally, the gains are used as a metric in an optimization framework to design parameterized balancing mechanisms within a given configuration space. Effectively, this enables an optimization of how well a system could balance without the need to pre-specify or co-generate controllers and/or trajectories. To validate the control contributions, simulated bipeds are subjected to external disturbances while standing still and walking. For the gain contributions, the framework is used to compare gain-optimized mechanisms to those based on the cost of transport metric. Through the combination of gain-based physical design optimization and the use of predictive, real-time balance point estimators within dynamic controllers, bipeds and other legged systems will soon be able to achieve reliable balance and gait in the real world

Generación de trayectorias para el tren inferior del robot humanoide TEO subiendo escaleras

Este trabajo forma parte de la labor realizada en el desarrollo del nuevo humanoide TEO por el grupo de trabajo Robotic Lab de la Universidad Carlos III de Madrid. Una importante actividad en el de desarrollo de este humanoide es dotarlo de movilidad y autonomía. Se espera que sea capaz de andar y subir escaleras. Este proyecto en concreto se centra en la generación de trayectorias, partiendo de un esquema elemental de un sistema de control cinemático, se ha desarrollado un conjunto de funciones que implementan este sistema para la generación de trayectorias para el tren inferior del robot humanoide TEO. A partir de la información sobre la plataforma bípeda y la planificación del paso que se va a realizar, se establece un conjunto de valores que tomarán las articulaciones en ciertos instantes de tiempo durante el movimiento. El objetivo de este trabajo es llevar a cabo la interpolación de estos valores articulares para dar como resultado las curvas que describen la posición de las articulaciones de la estructura durante todo el tiempo que dura el paso, condicionado por una serie de limitaciones articulares y de continuidad de las trayectorias. El esquema de desarrollo se pone a prueba con una planificación del movimiento que se realiza al subir una escalera, programando el conjunto de algoritmos en Matlab. De las pruebas realizadas se deriva la representación de trayectorias en el espacio típicas como las de la pelvis o de los pies, para verificar la ausencia de interferencia con el terreno, y una estimación de la solicitación en el tobillo en la pierna de apoyo, por ser la articulación que soporta todo el peso de la estructura.Ingeniería Industria