Angular displacement

About: Angular displacement is a research topic. Over the lifetime, 5102 publications have been published within this topic receiving 46081 citations. The topic is also known as: rotational displacement.

A Wide-Range Capacitive Sensor for Linear and Angular Displacement Measurement

Abstract: A new capacitive sensor that is suitable for measuring both linear and angular displacements of a shaft over a wide range is reported in this paper. The sensor consists of a cylindrical shaft with a semi-hollow cylinder attached in the center; the shaft is capable of moving along the axis as well as rotating about the axis. Two pairs of semi-hollow-cylindrical electrodes surround the shaft, which is grounded. The amount of linear displacement and rotation is calculated by measuring the change in the capacitance of each of the four electrodes with respect to the shaft. A prototype sensor was constructed and tested; the rms error obtained is 0.6% for the linear displacement and less than 0.6% for the angular displacement. The proposed sensor has potential applications in several robotic, industrial, and automotive fields.

Estimation of self-turning in the dark: comparison between active and passive rotation.

Abstract: The present work compares passive and active rotations in darkness with the aim of characterizing the contribution of efferent and proprioceptive information to the perception of angular displacement The perception of angular displacements was measured in 12 naive subjects (Ss), who either stood on a rotating platform (passive mode, P) or actively turned about their vertical axis by stepping around ”on the spot” on a stationary platform (active mode, A) Rotations consisted of short acceleration epochs followed by constant velocity periods of 185, 37, and 55°/s, with angular displacements ranging from 30° to 810° (presented in a randomized order); in the case of active turning, Ss had learned to approximately produce any of these three velocity levels on command Ss indicated perceived displacement either verbally (verbal estimation mode, E), or by stopping their rotation when self-displacement appeared to match the magnitude specified by the experimenter (targeting, T) The resulting four conditions (PE, PT, AE, AT) were administered blockwise In none of the four conditions was there a systematic dependence of perception on turning velocity Therefore, the results were pooled across velocities, and the Ss’ performance was summarized in the form of estimation curves showing median estimates as a function of physical displacement There were several differences between the passive and active modes: AE- and AT-estimation curves were linear, close to veracity, and fairly similar to each other In contrast, the PE-curve was curved rightwardly (”saturation”), with small displacements being overestimated and large ones underestimated, whereas the PT-curve was linear and indicated a pronounced overestimation of large displacements Moreover, both the random and the systematic errors (measures of individual consistency and correctness of individual calibration, respectively) were significantly smaller in the active than in the passive modes The observed independence of Ss’ perception from turning velocity also during passive rotation suggests that the perceptual time constant was significantly longer than 16 s (a value cited as typical for vestibular perception), being possibly ”enhanced” by contextual implications and by expectations of the Ss The clear improvement of perceptual performance in the active mode testifies to the importance of the efferent and proprioceptive signals arising during active motion On the assumption that these signals are about as ”noisy” as the vestibular ones, the smaller errors during active turning could result from their combination with the vestibular signal Alternatively, they could also be intrinsically less noisy than the vestibular signal and simply replace the latter during active motion In the context of these alternatives (which are not exhaustive), the general problem of sensory fusion is discussed, that is, by which mechanisms are signals from different sensory sources combined to obtain a unified representation of the self’s orientation

Vision-based six-degree-of-freedom computer input device

Abstract: A vision-based controller provides translational and rotational control signals to a computer or other input driven device. The controller includes a tracked object, positioned in space and having at least a first reference point and a second reference point. The tracked object is capable of three dimensional rotational and translational movement. At least one imaging device, positioned at a distance from the tracked object, generates an image of the tracked object, at plural succeeding times. A processor unit receives the image, comprised of pixel values, from the imaging device; identifies pixels corresponding to a current center of the tracked object, the first reference point and the second reference point; determines a current dimension (i.e., size or radius) of the tracked object; calculates a translational and rotational displacement of the tracked object based on the above information; and generates control signals in accordance with the transitional and rotational displacement.

Sensorless control of permanent magnet synchronous motors

Abstract: The paper deals with the control of permanent magnet synchronous motors without any mechanical sensor. For this purpose a new flux model (“INFORM model”) is used, working properly at each operating condition, especially at low angular velocity. At higher angular velocity, an e.m.f.-based model is used. A Kalman filter estimates the angular position, the angular velocity and the torque. An optimal state controller is presented which yields good dynamic performance. The system is realized on a digital signal processor.