Use of accelerometers in the control of practical prosthetic arms

Accelerometers can be used to augment the control of powered prosthetic arms. They can detect the orientation of the joint and limb and the controller can correct for the amount of torque required to move the limb. They can also be used to create a platform, with a fixed orientation relative to gravity for the object held in the hand. This paper describes three applications for this technology, in a powered wrist and powered arm. By adding sensors to the arm making these data available to the controller, the input from the user can be made simpler. The operator will not need to correct for changes in orientation of their body as they move. Two examples of the correction for orientation against gravity are described and an example of the system designed for use by a patient. The controller for all examples is a distributed set of microcontrollers, one node for each joint, linked with the Control Area Network (CAN) bus. The clinical arm uses a version of the Southampton Adaptive Manipulation Scheme to control the arm and hand. In this control form the user gives simpler input commands and leaves the detailed control of the arm to the controller

Developing a Low-cost MEMS IMU/ DGPS Integrated System for Robust Machine Automation

A navigation system based on a low-cost, low-grade MEMS inertial measurement unit (IMU) integrated with differential GPS has been developed for machine automation applications. Because the inertial sensors have no ability to measure Earth rotation, the attitude errors of pitch and heading cannot be obtained using only IMU measurements. To overcome this deficiency, two Kalman filters are used for robust estimation of navigation parameters and the errors of inertial sensors. An adaptive fading factor Kalman filter uses a GPS dynamic model to generate the velocities and accelerations which can be used to acquire approximate pitch and heading values. Another Kalman filter is used to integrate position, velocity and attitude from both the IMU and GPS so that position and attitude can be estimated directly - due to their individual observabilities. The drift error of the inertial sensors is also well compensated. The proposed algorithm has been implemented into post-processing integration software and has been tested in the field. The test results demonstrated that this robust MEMS/DGPS integrated system has the capability of providing continuous and reliable navigation for machine automation applications

Блочная калибровка инерциально-измерительного модуля

Представлено новий метод калібрування інерціальних вимірювальних блоків для безплатформової інерціальної технології. Інерціальний вимірювальний блок складається з акселерометрів, гіроскопів і системи обробки сигналів. Як правило, для калібрування інерціального вимірювального блоку використовують метод тестових поворотів та обертання на поворотному столі. Новий метод калібрування основано на вимірюванні повного кута повороту або кінцевого обертання. Фактично пропонується повертати інерціальний вимірювальний блок навколо одної осі кінцевого повороту. Для розв’язання рівняння калібрування необхідно забезпечити рівність рангу основної матриці порядку базової матриці. Результати змодельованих даних ІВБ представлено для демонстрації ефективності нового методу калібрування.A new calibration method is proposed for the inertial measurement units of strapdown inertial technology. Such a block consists of accelerometers, gyroscopes and a signal processing system. As a rule, the method of test turnings and rotations on rotary table is used for calibration of the inertial measurement unit. The new method is based on measurement of the full angle of turning or the final rotation. In fact, it is proposed to turn the inertial measurement unit around the axis of final rotation. To solve the equation of calibration, it is necessary to provide the equality of the rank and order of basic matrix. The results of modeling data demonstrate an efficiency of new method of calibration

Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors

Low cost robots, such as vacuum cleaners or lawn mowers, employ simplistic and often random navigation policies. Although a large number of sophisticated localization and planning approaches exist, they require additional sensors like LIDAR sensors, cameras or time of flight sensors. In this work, we propose a global localization method biologically inspired by simple insects, such as the ant Cataglyphis that is able to return from distant locations to its nest in the desert without any or with limited perceptual cues. Like in Cataglyphis, the underlying idea of our localization approach is to first compute a pose estimate from pro-prioceptual sensors only, using land navigation, and thereafter refine the estimate through a systematic search in a particle filter that integrates the rare visual feedback. In simulation experiments in multiple environments, we demonstrated that this bioinspired principle can be used to compute accurate pose estimates from binary visual cues only. Such intelligent localization strategies can improve the performance of any robot with limited sensing capabilities such as household robots or toys.Comment: Accepted to BIOSIGNALS 201

3D-Calibration of the IMU

International audienceA new calibration method for Inertial Measurement Unit (IMU) of strapdown inertial technology was presented. IMU has been composed of accelerometers, gyroscopes and a circuit of signal processing. Normally, a rate transfer test and multi-position tests are used for IMU calibration. The new calibration method is based on whole angle rotation or finite rotation. In fact it is suggested to turn over IMU around three axes simultaneously. In order to solve the equation of calibration, it is necessary to provide an equality of a rank of basic matrix into degree of basic matrix. The results of simulated IMU data presented to demonstrate the performance of the new calibration method

Anti-disturbance fault tolerant initial alignment for inertial navigation system subjected to multiple disturbances

Modeling error, stochastic error of inertial sensor, measurement noise and environmental disturbance affect the accuracy of an inertial navigation system (INS). In addition, some unpredictable factors, such as system fault, directly affect the reliability of INSs. This paper proposes a new anti-disturbance fault tolerant alignment approach for a class of INSs sub- jected to multiple disturbances and system faults. Based on modeling and error analysis, stochastic error of inertial sensor, measurement noise, modeling error and environmental disturbance are formulated into different types of disturbances described by a Markov stochastic process, Gaussian noise and a norm-bounded variable, respectively. In order to improve the accuracy and reliability of an INS, an anti-disturbance fault tolerant filter is designed. Then, a mixed dissipative/guarantee cost performance is applied to attenuate the norm-bounded disturbance and to optimize the estimation error. Slack variables and dissipativeness are introduced to reduce the conservatism of the proposed approach. Finally, compared with the unscented Kalman filter (UKF), simulation results for self-alignment of an INS are provided based on experimental data. It can be shown that the proposed method has an enhanced disturbance rejection and attenuation performance with high reliability

Estimation of forward accelerometer parameter using lateral acceleration and Kalman filtering

In this text, some initial work on the development of an autonomous vehicle is presented. A simplified vehicle dynamics model is used to define the relationship between front steering angle and turn radius. A discrete time model is also developed for the accelerometer system to be identified. The vehicle dynamics and simulations used in this work are presented and used to verify the steer angle relationship derived earlier. The Kalman filter is applied to a scalar signal before being used with future analysis. Simulated accelerometer signals corrupted with noise were used to generate four experimental cases. These signals were used to calculate the system states, which were sent into the Kalman filter to minimize the error between the state model and accelerometer output. The results of the Kalman filter were applied, along with the steer angle and turn radius relationship, in order to provide an estimate of the signal offset of the longitudinal accelerometer. In most cases, this system and extended Kalman filter did quite well at extracting the parameter information at low drive velocities regardless of changes in front steering angle

Development of a Sensing System for Underground Optic Fiber Cable Conduit Mapping

The motivation of this research is to obtain an accurate three-dimensional (3D) layout of an underground conduit, which may be beneficial to optic fiber cable installers and engineers. A newly designed algorithm for 3D position tracking with the help of an inertial sensor and an encoder has been developed. Two types of representations (Euler angle and Quaternion) for orientation and rotation are also introduced, followed by several data pre-processing procedures. A sensing fusion method is utilized to overcome the accumulated errors introduced by the sensor drifting. Considering the application of 3D underground duct mapping in this research, a sensing system using the newly designed algorithm was designed and analyzed. Additional information, such as the orientation and position of the starting and ending points, are integrated into the algorithm to correct the sensing drifting and refine the position estimation. To verify and demonstrate the design of the algorithm and sensing system for 3D underground duct mapping, an experimental test-bed based on the sensing system design, which consists of an IMU, a duct rodder and a fiber blower, was developed. Experiments on three different layouts of the conduit were conducted and analyzed to demonstrate the feasibility and efficiency of the newly developed algorithm and the sensing system design