Objective estimation of pain based on facial expression,vital signs and body movements

An intelligent automaton should always arrive at its goal automatically while avoiding the obstacles in a two-dimensional (2D) world. If the automaton does not know the shape or location of any obstacle in the world, it gathers information on its neighbourhood from some sensor, and according to the sensor information, it avoids the closer obstacles. In this situation, a sensor-based path-planning algorithm is used to determine the automaton's action flexibly according to changes in the sensor information. By this method, the automaton usually avoids the closer obstacles on the basis of the local information but it may circulate around some of the obstacles in the world because of the locality of the sensor information. If deadlock occurs, the automaton does not arrive at the goal at all. To overcome this drawback, we address a sufficient condition for designing a family of deadlock-free sensor-based path-planning algorithms in an uncertain world. Within this family, the automaton basically goes straight to the goal. If the automaton occasionally finds a hit point against an unfamiliar obstacle via the touch sensor, it traces the obstacle by touch and in time it finds a way to go straight to the goal again around the obstacle. Even under those conditions the automaton continues to trace the obstacle until its Euclidean distance to the goal is smaller than a distance index which is decreasing asymptotically. This is the sufficient condition, under which the automaton leaves the obstacle to go straight to the goal. This asymptotical approach of the leave point to the goal guarantees that the algorithm family will be deadlock-free. In the family, the automaton always goes straight to the goal if it does not trace any obstacle in the world. Thus, if the leave point comes asymptotically close to the goal, the circular space where the automaton can hit some obstacle in future decreases asymptotically. Therefore the circular space finally goes out of existence and consequently the automaton arrives at the goal. As a result, the family ensures the convergence of the automaton to the goal in an uncertain 2D world.     

Intention-based walking support for paraplegia patients with Robot Suit HAL

This paper proposes an algorithm to estimate human intentions related to walking in order to comfortably and safely support a paraplegia patient's walk. Robot Suit HAL (Hybrid Assistive Limb) has been developed for enhancement of a healthy person's activities and for support of a physically challenged person's daily life. The assisting method based on bioelectrical signals such as myoelectricity successfully supports a healthy person's walking. These bioelectrical signals, however, cannot be measured properly from a paraplegia patient. Therefore another interface that can estimate a patient's intentions without any manual controller is desired for robot control since a manual controller deprives a patient of his/her hand freedom. Estimation of a patient's intentions contributes to providing not only comfortable support but also safe support, because any inconformity between the robot suit motion and the patient motion results in his/her stumbling or falling. The proposed algorithm estimates a patient's intentions from a floor reaction force (FRF) reflecting a patient's weight shift during walking and standing. The effectiveness of this algorithm is investigated through experiments on a paraplegia patient who has a sensory paralysis on both legs, especially his left leg. We show that HAL supports the patient's walk properly, estimating his intentions based on the FRF, while he keeps his own balance by himself.     

Simultaneous Localization of a Mobile Robot and Multiple Sound Sources Using a Microphone Array

Sound source localization is an important function in robot audition. Most existing works perform sound source localization using static microphone arrays. This work proposes a framework that simultaneously localizes the mobile robot and multiple sound sources using a microphone array on the robot. First, an eigenstructure-based generalized cross-correlation method for estimating time delays between microphones under multi-source environments is described. Using the estimated time delays, a method to compute the farfield source directions as well as the speed of sound is proposed. In addition, the correctness of the sound speed estimate is utilized to eliminate spurious sources, which greatly enhances the robustness of sound source detection. The arrival angles of the detected sound sources are used as observations in a bearing-only simultaneous localization and mapping procedure. As the source signals are not persistent and there is no identification of the signal content, data association is unknown and it is solved using the FastSLAM algorithm. The experimental results demonstrate the effectiveness of the proposed method.     

Image-based predictive display for high d.o.f. uncalibrated tele-manipulation using affine and intensity subspace models

The addition of immediate but estimated visual feedback, called predictive display, improves tele-manipulaton performance when the real video feedback is delayed. Current systems typically rely upon a previously calibrated camera and manipulator. We present a method where the motor-visual calibration is estimated on-line from motor commands and returned video images only. Predicted visual feedback is presented in two forms. As soon as a basic model has been estimated, a wire frame drawing of the predicted current pose is overlaid on the delayed video feedback. After some time when a rich model has been estimated, predicted intensity images are synthesized and these replace the delayed real video. In an intermediate situation where blurry synthesized images can be computed, the wireframe is overlaid on the synthesized images to show precisely the pose of the object. Experiments with a Utah/MIT robot hand and PUMA robot arm are shown.     

Seam tracking based on estimation of weld position using Kalman filtering

Abstract

A seam tracking method is presented based on the estimation of weld position during the gas tungsten arc welding process. Kalman filtering of the weld pool images from a visual sensor is applied to compute recursively the solution to the weld position equations which are established based on an estimation of the centroid position of the weld pool images. This centroid, the position of which corresponds with the weld position, is extracted as the measurement eigenvector. The evolution of the weld position data from the weld pool images can be described through an appropriate process model, so that the weld position can be detected by applying a Kalman filter. This allows adjustment of the welding torch position in real time, which may significantly reduce processing time and promote seam tracking accuracy. Simulations and actual welding experiments have demonstrated the effectiveness of the proposed algorithm in the presence of weld pool image noise and have demonstrated the robustness of weld position detection for seam tracking.     

Towards a Smooth Human–Robot Interaction for Rehabilitation Robotic Systems

The goal of this work is to develop a control framework to provide assistance to the subjects in such a manner that the interaction between the subjects and a robot-assisted rehabilitation system is smooth during the rehabilitation therapy. In order to achieve smoothness of interaction, a control framework is designed in such a way that it can automatically adjust the control gains of the robot-assisted rehabilitation system to modify the interaction dynamics between the system and the subject. An artificial neural network (ANN)-based proportional–integral (PI) gain scheduling controller is proposed to automatically determine the appropriate control gains for each individual subject. The human arm model is integrated with the ANN-based PI gain scheduling controller where the ANN uses estimated human arm parameters to select the appropriate PI gains for each subject such that the resultant interaction dynamics between the subject and the robot-assisted rehabilitation system could result in smooth interaction. Experimental results involving unimpaired subjects on a PUMA robot-based rehabilitation system are presented to demonstrate the efficacy of the proposed ANN-based PI gain scheduling controller on unimpaired subjects.     

Strength estimation of self-piercing rivets using lower bound limit load analysis

Abstract

This paper summarises the authors' work on strength and failure mode estimation of self-piercing rivets (SPRs) for automotive applications. First, the static cross tension strength of an SPR joint is estimated using a lower bound limit load based strength estimator. Failure mode associated with the predicted failure strength can also be identified. It is shown that the cross tension strength of an SPR joint depends on the material and gage combinations, rivet design, die design and riveting direction. The analytical rivet strength estimator is then validated by experimental rivet strength measurements and failure mode observations from nine SPR joint populations with various material and gage combinations. Next, the estimator is used to optimise rivet strength. Two illustrative examples are presented in which rivet strength is improved by changing rivet length and riveting direction from the original manufacturing parameters.     

Sonar-based guidance of unmanned underwater vehicles

This paper addresses the problem of the design and coordination of guidance and sonarbased motion estimation algorithms for unmanned underwater vehicles. In the framework of a two-layered hierarchical architecture uncoupling the system's dynamics and kinematics, a couple of guidance laws for approaching a target with the desired orientation and following an environmental feature have been designed with Lyapunov-based techniques. Suitable acoustic-based estimators of the corresponding operational variables have been designed and integrated with the guidance and control system. A finite state machine combined with a suitable interface for event generation allows the coordinated execution of basic guidance and motion estimation tasks to carry out more complex functions. Experimental results of pool trials of a prototype unmanned underwater vehicle executing free-space maneuvering, wall-following tasks and the more complex mission of following the perimeter of the trial pool are reported and discussed.     

Wrist Camera-Based Vibration Suppression Control for a Flexible Manipulator

This paper addresses a vision-based method for estimating vibration excited in the tip of a flexible-link manipulator. In this method, estimation of vibration is achieved by observing the variation of image features projected on a wrist camera. It mimics the situation of utilizing a wrist camera in tip vibration control of a space manipulator. In space, a vision sensor can be expected to be a feasible means for measuring the elastic vibration of the space manipulators, since they are more reliable compared with sensors like strain gauges. The method proposed in this paper takes advantage of the frequential characteristics of visual information that are reflected as a blurred background scene. With the high-frequency component of the projected image features, a Kalman filter-based observer is implemented as the estimator for the vibration. This implementation is characterized by the considerations of incorporating the slow sensor of the camera in the fast servo loop and compensation of the time delay due to image processing. With the vibration estimator, vibration suppression control relying solely on a wrist camera becomes possible. This scheme is successfully verified by experiments.     

Omnidirectional vision-based ego-pose estimation for an autonomous in-pipe mobile robot

This paper describes the omnidirectional vision-based ego-pose estimation method of an in-pipe mobile robot. An in-pipe mobile robot has been developed for inspecting the inner surface of various pipeline configurations, such as the straight pipeline, the elbow and the multiple-branch. Because the proposed in-pipe mobile robot has four individual drive wheels, it has the ability of flexible motions in various pipelines. The ego-pose estimation is indispensable for the autonomous navigation of the proposed in-pipe robot. An omnidirectional camera and four laser modules mounted on the mobile robot are used for ego-pose estimation. An omnidirectional camera is also used for investigating the inner surface of the pipeline. The pose of the in-pipe mobile robot is estimated from the relationship equation between the pose of a robot and the pixel coordinates of four intersection points where light rays that emerge from four laser modules intersect the inside of the pipeline. This relationship equation is derived from the geometry analysis of an omnidirectional camera and four laser modules. In experiments, the performance of the proposed method is evaluated by comparing the result of our algorithm with the measurement value of a specifically designed sensor, which is a kind of a gyroscope.