326 research outputs found

    Contact-Aided Invariant Extended Kalman Filtering for Legged Robot State Estimation

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    This paper derives a contact-aided inertial navigation observer for a 3D bipedal robot using the theory of invariant observer design. Aided inertial navigation is fundamentally a nonlinear observer design problem; thus, current solutions are based on approximations of the system dynamics, such as an Extended Kalman Filter (EKF), which uses a system's Jacobian linearization along the current best estimate of its trajectory. On the basis of the theory of invariant observer design by Barrau and Bonnabel, and in particular, the Invariant EKF (InEKF), we show that the error dynamics of the point contact-inertial system follows a log-linear autonomous differential equation; hence, the observable state variables can be rendered convergent with a domain of attraction that is independent of the system's trajectory. Due to the log-linear form of the error dynamics, it is not necessary to perform a nonlinear observability analysis to show that when using an Inertial Measurement Unit (IMU) and contact sensors, the absolute position of the robot and a rotation about the gravity vector (yaw) are unobservable. We further augment the state of the developed InEKF with IMU biases, as the online estimation of these parameters has a crucial impact on system performance. We evaluate the convergence of the proposed system with the commonly used quaternion-based EKF observer using a Monte-Carlo simulation. In addition, our experimental evaluation using a Cassie-series bipedal robot shows that the contact-aided InEKF provides better performance in comparison with the quaternion-based EKF as a result of exploiting symmetries present in the system dynamics.Comment: Published in the proceedings of Robotics: Science and Systems 201

    Review of Anthropomorphic Head Stabilisation and Verticality Estimation in Robots

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    International audienceIn many walking, running, flying, and swimming animals, including mammals, reptiles, and birds, the vestibular system plays a central role for verticality estimation and is often associated with a head sta-bilisation (in rotation) behaviour. Head stabilisation, in turn, subserves gaze stabilisation, postural control, visual-vestibular information fusion and spatial awareness via the active establishment of a quasi-inertial frame of reference. Head stabilisation helps animals to cope with the computational consequences of angular movements that complicate the reliable estimation of the vertical direction. We suggest that this strategy could also benefit free-moving robotic systems, such as locomoting humanoid robots, which are typically equipped with inertial measurements units. Free-moving robotic systems could gain the full benefits of inertial measurements if the measurement units are placed on independently orientable platforms, such as a human-like heads. We illustrate these benefits by analysing recent humanoid robots design and control approaches

    Humanoid odometric localization integrating kinematic, inertial and visual information

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    We present a method for odometric localization of humanoid robots using standard sensing equipment, i.e., a monocular camera, an inertial measurement unit (IMU), joint encoders and foot pressure sensors. Data from all these sources are integrated using the prediction-correction paradigm of the Extended Kalman Filter. Position and orientation of the torso, defined as the representative body of the robot, are predicted through kinematic computations based on joint encoder readings; an asynchronous mechanism triggered by the pressure sensors is used to update the placement of the support foot. The correction step of the filter uses as measurements the torso orientation, provided by the IMU, and the head pose, reconstructed by a VSLAM algorithm. The proposed method is validated on the humanoid NAO through two sets of experiments: open-loop motions aimed at assessing the accuracy of localization with respect to a ground truth, and closed-loop motions where the humanoid pose estimates are used in real-time as feedback signals for trajectory control

    Stabilizer architecture for humanoid robots collaborating with humans

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    Hoy en día, los avances en las tecnologías de información y comunicación permiten el uso de robots como compañeros en las actividades con los seres humanos. Mientras que la mayoría de las investigaciones existentes se dedica a la interacción entre humanos y robots, el marco de esta investigación está centrado en el uso de robots como agentes de colaboración. En particular, este estudio está dedicado a los robots humanoides que puedan ayudar a la gente en varias tareas en entornos de trabajo. Los robots humanoides son sin duda los m as adecuados para este tipo de situaciones: pueden usar las mismas herramientas que los seres humanos y son lo m as probablemente aceptados por ellos. Después de explicar las ventajas de las tareas de colaboración entre los humanos y los robots y las diferencias con respecto a los sistemas de interacción y de teleoperación, este trabajo se centra en el nivel de las tecnologías que es necesario para lograr ese objetivo. El problema más complicado en el control de humanoides es el balance de la estructura. Este estudio se centra en técnicas novedosas para la estimación de la actitud del robot, que se utilizarán para el control. El control del robot se basa en un modelo muy conocido y simplificado: el péndulo invertido. Este modelo permite tener un control en tiempo real sobre la estructura, mientras que esté sometida a fuerzas externas / disturbios. Trayectorias suaves para el control de humanoides se han propuesto y probado en plataformas reales: éstos permiten reducir los impactos del robot con su entorno. Finalmente, el estudio extiende estos resultados a una contribución para la arquitectura de colaboración humano-humanoide. Dos tipos de colaboraciones humano humanoide se analizan: la colaboración física, donde robots y humanos comparten el mismo espacio y tienen un contacto físico (o por medio de un objeto), y una colaboración a distancia, en la que el ser humano está relativamente lejos del robot y los dos agentes colaboran por medio de una interfaz. El paradigma básico de esta colaboración robótica es: lo que es difícil (o peligroso) para el ser humano se hace por medio del robot y lo que es difícil para el robot lo puede mejor hacer el humano. Es importante destacar que el contexto de los experimentos no se basa en una unica plataforma humanoide; por el contrario, tres plataformas han sido objeto de los experimentos: se han empleado los robots HOAP-3, HRP-2 y TEO. ----------------------------------------------------------------------------------------------------------------------------------------------------------Nowadays, the advances in information and communication technologies permit the use of robots as companions in activities with humans. While most of the existing research is dedicated to the interaction between humans and robots, the framework of this research is the use of robots as collaborative agents. In particular, this study is dedicated to humanoid robots which should assist people in several tasks in working environments. Humanoid robots are certainly the most adequate for such situations: they can use the same tools as humans and are most likely accepted by them. After explaining the advantages of collaborative tasks among humans and robots and the differences with respect to interaction and teleoperation systems, this work focuses on the level of technologies which is necessary in order to achieve such a goal. The most complicated problem in humanoid control is the structure balance. This study focuses in novel techniques in the attitude estimation of the robot, to be used for the control. The control of the robot is based on a very well-known and simplified model: the double inverted pendulum. This model permits having a real-time control on the structure while submitted to external forces/disturbances. The control actions are strongly dependent on the three stability regions, which are determined by the position of the ZMP in the support polygon. Smooth trajectories for the humanoid control have been proposed and tested on real platforms: these permit reducing the impacts of the robot with its environment. Finally, the study extends these results to a contribution for human-humanoid collaboration architecture. Two types of human-humanoid collaborations are analyzed: a physical collaboration, where robot and human share the same space and have a physical contact (or by means of an object), and a remote collaboration, in which the human is relatively far away from the robot and the two agents collaborate using an interface. The basic paradigm for this robotic collaboration is: what is difficult (or dangerous) for the human is done by the robot and what is difficult for the robot is better done by the human. Importantly, the testing context is not based on a single humanoid platform; on the contrary, three platforms have been object of the experiments: the Hoap-3, HRP-2 and HRP2 robot have been employed

    Open motion control architecture for humanoid robots

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    This Ph.D. thesis contributes to the development of control architecture for robots. It provides a complex study of a control systems design and makes a proposal for generalized open motion control architecture for humanoid robots. Generally speaking, the development of humanoid robots is a very complex engineering and scientific task that requires new approaches in mechanical design, electronics, software engineering and control. First of all, taking into account all these considerations, this thesis tries to answer the question of why we need the development of such robots. Further, it provides a study of the evolution of humanoid robots, as well as an analysis of modern trends. A complex study of motion, that for humanoid robots, means first of all the biped locomotion is addressed. Requirements for the design of open motion control architecture are posed. This work stresses the motion control algorithms for humanoid robots. The implementation of only servo control for some types of robots (especially for walking systems) is not sufficient. Even having stable motion pattern and well tuned joint control, a humanoid robot can fall down while walking. Therefore, these robots need the implementation of another, upper control loop which will provide the stabilization of their motion. This Ph.D. thesis proposes the study of a joint motion control problem and a new solution to walking stability problem for humanoids. A new original walking stabilization controller based on decoupled double inverted pendulum dynamical model is developed. This Ph.D. thesis proposes novel motion control software and hardware architecture for humanoid robots. The main advantage of this architecture is that it was designed by an open systems approach allowing the development of high-quality humanoid robotics platforms that are technologically up-to-date. The Rh-1 prototype of the humanoid robot was constructed and used as a test platform for implementing the concepts described in this Ph.D. thesis. Also, the implementation of walking stabilization control algorithms was made with OpenHRP platform and HRP-2 humanoid robot. The simulations and walking experiments showed favourable results not only in forward walking but also in turning and backwards walking gaits. It proved the applicability and reliability of designed open motion control architecture for humanoid robots. Finally, it should be noted that this Ph.D. thesis considers the motion control system of a humanoid robot as a whole, stresses the entire concept-design-implementation chain and develops basic guidelines for the design of open motion control architecture that can be easily implemented in other biped platforms
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