Mag and Accelerometers to Calculate Robot Parameters

Question: Discuss about the Mag and Accelerometers to Calculate Robot Parameters. Answer: Literature Review of the Article In this article, the author has tried to analyse the importance and applications of IMU (Inertial Measurement Technology) from ergonomic to industrial, life sciences to biochemical and animation to reality. According to Langfelder et al. (2013), in medical field, instruments have greater significance to measure robotic and human angle including acceleration, torque and angular velocity. The major reasons to use this technology in every field are its ease of usability, light weight and smooth operation. In support to that, Lategahn et al. (2013) opined that Inertial Measurement Unit (IMU) is comprised of advanced tools such as accelerometers, gyroscopes and magnetometer which help to track translational and rotational movements. It is also found out that this IMU can measure both earth's magnetic field as well as the direction of gravity. Each of the components of IMU has been described in detailed and precise manner. This accelerator is categorised by two sensors one is mechanical an d other is solid state sensors. Oberlander (2016) showed that gyroscopes could measure angular displacement or velocity along a single sensitive axis. These gyroscopes also have different varieties such as silicon gyroscopes, vibratory gyroscopes, mechanical gyroscopes and others. In the last section of the article, magnetometer has been described which is used for two reasons, one is to measure the strength, and another is to measure magnetisation of the magnetic field. On the other hand, Lategahn et al. (2013) cited that the devices have proved to be efficient for calculating the different movements of both the human and robots including hip joints and wrists. In addition, extension and flexion of the elbow with relative movement can also be measured through these instruments. On a contrary Hoflinger et al. (2013) showed that it is not possible to calculate all the joint angles of shoulders due to its complex stability and mobility. Oberlander (2016) concluded that these instrumen ts are useful for the treatment of clinical disorders and medical diagnosis of the patients as it can measure complex angles between hip, wrist and shoulder joints. This article has also demonstrated various formulas and algorithms that can help to calculate robotically as well as human angles with these different sensors which help to find out acceleration, torque and angular velocity for smooth and reliable operations. Joint Angle Tracking with Inertial Sensors (El-Gohary 2013) Literature Review of the Article The paper concerns with the characterization of both normal and pathological human movement to develop tracking devices using inertial sensors. According to Kapoor, and Ohri (2013), kinematic models are combined for designing and controlling robotic arms using various state space methods for estimating different angles. More specifically, this technique can be applied to measure the angles of human elbow and shoulder by using wireless and wearable inertial measurement units (IMU). Akhter and Black (2015) showed the integration of the angular velocity for calculating the changes in the orientation of the robotic arms. In support to this, Gillett, Barrett, and Lichtwark (2013) showed, if the measured angular velocity contains even relatively minor error or drift, it can lead to large integration errors. The device essentially consists of triaxial accelerometers and triaxial magnetometers. Furthermore, the observation model demonstrates the measures obtained by the triaxial acceleromete r for the translational acceleration and the triaxial gyroscope for the angular rate. Kapoor, and Ohri (2013) showed that the applied algorithm generates large measurement equations and application of the arm kinematic model parameters to the Newton-Euler equations. However, the paper additionally includes a comparison and contrast between the true robot joint angles and their estimate using the inertial tracker with the modified kinematic equations. According to Akhter and Black (2015) accelerometers, gyroscopes and the electronic sensors are corrupted by random noise. On the other hand, a fusion of magnetometers with the inertial sensors is useful in demonstrating enhanced performance when the magnetic field disturbances are absent. (El-Gohary 2013) has utilised the unscented Kalman filter with the modified system equations for estimating human elbow, shoulder and wrist joint angles from a robot arm. The extended Kalman filter has been used to approximate the nonlinear process and measurement operations by Taylor series expansion method. Hence, the IMU sensors offer a low cost and practical alternative to motion capture systems. The state space framework enables an efficient calculation of the angular velocity. (El-Gohary 2013) showed in this support that the system performance is tracked and monitored by comparing the joint angles that are estimated by the inertial tracker with the ones that are typically estimated by an optical tracking reference system. Therefore, the paper reviews the algorithm that combines kinematic models for controlling robotic movements and estimation of human joint angles. References El-Gohary, M., 2013. Joint Angle Tracking with Inertial Sensors. [online] https://pdxscholar.library.pdx.edu/. Available at: https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=1660context=open_access_etds [Accessed 11 Aug. 2013]. Hoflinger, F., Mller, J., Zhang, R., Reindl, L.M. and Burgard, W., 2013. A wireless micro inertial measurement unit (IMU). IEEE Transactions on Instrumentation and Measurement, 62(9), pp.2583-2595. Langfelder, G., Buffa, C., Frangi, A., Tocchio, A., Lasalandra, E. and Longoni, A., 2013. Z-axis magnetometers for MEMS inertial measurement units using an industrial process. IEEE Transactions on Industrial Electronics, 60(9), pp.3983-3990. Lategahn, H., Schreiber, M., Ziegler, J. and Stiller, C., 2013, June. Urban localization with camera and inertial measurement unit. In Intelligent Vehicles Symposium (IV), 2013 IEEE (pp. 719-724). IEEE. Oberlander, K., 2016. Inertial Measurement Unit (IMU) Technology. [online] https://www.noraxon.com/. Available at: https://www.noraxon.com/wp-content/uploads/2015/09/IMU-Tech-Report.pdf [Accessed 11 Aug. 2015].