Unsupervised Contact Learning for Humanoid Estimation and Control

This work presents a method for contact state estimation using fuzzy clustering to learn contact probability for full, six-dimensional humanoid contacts. The data required for training is solely from proprioceptive sensors - endeffector contact wrench sensors and inertial measurement units (IMUs) - and the method is completely unsupervised. The resulting cluster means are used to efficiently compute the probability of contact in each of the six endeffector degrees of freedom (DoFs) independently. This clustering-based contact probability estimator is validated in a kinematics-based base state estimator in a simulation environment with realistic added sensor noise for locomotion over rough, low-friction terrain on which the robot is subject to foot slip and rotation. The proposed base state estimator which utilizes these six DoF contact probability estimates is shown to perform considerably better than that which determines kinematic contact constraints purely based on measured normal force.Comment: Submitted to the IEEE International Conference on Robotics and Automation (ICRA) 201

Process operating mode monitoring : switching online the right controller

This paper presents a structure which deals with process operating mode monitoring and allows the control law reconfiguration by switching online the right controller. After a short review of the advances in switching based control systems during the last decade, we introduce our approach based on the definition of operating modes of a plant. The control reconfiguration strategy is achieved by online selection of an adequate controller, in a case of active accommodation. The main contribution lies in settling up the design steps of the multicontroller structure and its accurate integration in the operating mode detection and accommodation loop. Simulation results show the effectiveness of the operating mode detection and accommodation (OMDA) structure for which the design steps propose a method to study the asymptotic stability, switching performances improvement, and the tuning of the multimodel based detector

Trajectory generation for multi-contact momentum-control

Simplified models of the dynamics such as the linear inverted pendulum model (LIPM) have proven to perform well for biped walking on flat ground. However, for more complex tasks the assumptions of these models can become limiting. For example, the LIPM does not allow for the control of contact forces independently, is limited to co-planar contacts and assumes that the angular momentum is zero. In this paper, we propose to use the full momentum equations of a humanoid robot in a trajectory optimization framework to plan its center of mass, linear and angular momentum trajectories. The model also allows for planning desired contact forces for each end-effector in arbitrary contact locations. We extend our previous results on LQR design for momentum control by computing the (linearized) optimal momentum feedback law in a receding horizon fashion. The resulting desired momentum and the associated feedback law are then used in a hierarchical whole body control approach. Simulation experiments show that the approach is computationally fast and is able to generate plans for locomotion on complex terrains while demonstrating good tracking performance for the full humanoid control

Humanoid Momentum Estimation Using Sensed Contact Wrenches

This work presents approaches for the estimation of quantities important for the control of the momentum of a humanoid robot. In contrast to previous approaches which use simplified models such as the Linear Inverted Pendulum Model, we present estimators based on the momentum dynamics of the robot. By using this simple yet dynamically-consistent model, we avoid the issues of using simplified models for estimation. We develop an estimator for the center of mass and full momentum which can be reformulated to estimate center of mass offsets as well as external wrenches applied to the robot. The observability of these estimators is investigated and their performance is evaluated in comparison to previous approaches.Comment: Submitted to the 15th IEEE RAS Humanoids Conference, to be held in Seoul, Korea on November 3 - 5, 201

State Estimation for a Humanoid Robot

This paper introduces a framework for state estimation on a humanoid robot platform using only common proprioceptive sensors and knowledge of leg kinematics. The presented approach extends that detailed in [1] on a quadruped platform by incorporating the rotational constraints imposed by the humanoid's flat feet. As in previous work, the proposed Extended Kalman Filter (EKF) accommodates contact switching and makes no assumptions about gait or terrain, making it applicable on any humanoid platform for use in any task. The filter employs a sensor-based prediction model which uses inertial data from an IMU and corrects for integrated error using a kinematics-based measurement model which relies on joint encoders and a kinematic model to determine the relative position and orientation of the feet. A nonlinear observability analysis is performed on both the original and updated filters and it is concluded that the new filter significantly simplifies singular cases and improves the observability characteristics of the system. Results on simulated walking and squatting datasets demonstrate the performance gain of the flat-foot filter as well as confirm the results of the presented observability analysis.Comment: IROS 2014 Submission, IEEE/RSJ International Conference on Intelligent Robots and Systems (2014) 952-95

Factors influencing the holding power of the school

The holding power of\u27 the school is justified and bolstered by many factors which stem from our faith in formal education. This is quite generally regarded as a basic method not only tor acquiring ideas and techniques but tor the development of personality and the qualities of good citizenship. Formal education is part of our mores. It is an indispensable social adjustment to the increasing demands of our specialized and technological society. Nevertheless, in spite of the pressure of\u27 public opinion, the dependence of modern society upon formal education, and the efforts of the law and of the school to keep children in attendance long enough for them to enjoy the advantages of a formal education, there are still too many children who pass on to the status of adults without adequate training through the agency of the school

Fachadas mendocinas : la identidad de lo culto y lo popular

Fil: Rotella, María Inés. Universidad Nacional de Cuyo. Facultad de Artes y Diseñ

Finite Element Modeling of Microstructural Changes in Turning of AA7075-T651 Alloy and Validation

The surface characteristics of a machined product strongly influence its functional performance. During machining, the grain size of the surface is frequently modified, thus the properties of the machined surface are different to that of the original bulk material. These changes must be taken into account when modeling the surface integrity effects resulting from machining. In the present work, grain size changes induced during turning of AA 7075-T651 (160 HV) alloy are modeled using the Finite Element (FE) method and a user subroutine is implemented in the FE code to describe the microstructural change and to simulate the dynamic recrystallization, with the consequent formation of new grains. In particular, a procedure utilizing the Zener-Hollomon and Hall-Petch equations is implemented in the user subroutine to predict the evolution of the material grain size and the surface hardness when varying the cutting speeds (180 - 720 m/min) and tool nose radii (0.4 - 1.2 mm). All simulations were performed for dry cutting conditions using uncoated carbide tools. The effectiveness of the proposed FE model was demonstrated through its capability to predict grain size evolution and hardness modification from the bulk material to machined surface. The model is validated by comparing the predicted results with those experimentally observed