The effects of long-duration space exposure on the mechanical properties of some carbon-reinforced resin matrix composites

Long Duration Exposure Facility (LDEF) Experiment A0175 involved the non-instrumented exposure of seven carbon-fiber reinforced resin-matrix advanced composite panels contained in two trays - A7 and A1. These two trays were located, respectively, on the leading and trailing faces of LDEF, obliquely oriented to the RAM (Row 9) and WAKE (Row 3) directions. The identity and location of the seven panels, which consisted of six flat laminates of the following material systems are shown: carbon/epoxy (T300/934), carbon/bismaleimide (T300/F178), and carbon/polyimide (C6000/LARC-160 and C6000/PMR-15), plus one bonded honeycomb sandwich panel (T300/934 face sheets and Nomex core) patterned after the Space Shuttle payload bay door construction. These material systems were selected to represent a range of then-available matrix resins which, by virtue of their differing polymer chemistry, could conceivably exhibit differing susceptibility to the low-earth orbit (LEO) environment. The principal exposure conditions of the LDEF environment at these tray locations are shown. Noteworthy to some of the observations discussed is the four-orders-of magnitude difference in the atomic oxygen (AO) fluence, which made a shallow incidence angle (approximately 22 deg) to Tray A7, while Tray A1 on the trailing face was essentially shielded from AO exposure. This evaluation focused on determining the individual and relative suitability of a variety of resin-matrix composite systems for long-term space structural applications. This was accomplished primarily by measuring and comparing a range of engineering mechanical properties on over 300 test coupons sectioned from the flight panels and from identical control panels, and tested at ambient and elevated temperatures. This testing was supported by limited physical characterization, involving visual examination of flight panel surface features, measurements of weight loss and warpage, and examination for changes in internal integrity (micro cracking, delamination) by ultrasonic c-scan and polished cross-sections

Sliding mode control for robust and smooth reference tracking in robot visual servoing

[EN] An approach based on sliding mode is proposed in this work for reference tracking in robot visual servoing. In particular, 2 sliding mode controls are obtained depending on whether joint accelerations or joint jerks are considered as the discontinuous control action. Both sliding mode controls are extensively compared in a 3D-simulated environment with their equivalent well-known continuous controls, which can be found in the literature, to highlight their similarities and differences. The main advantages of the proposed method are smoothness, robustness, and low computational cost. The applicability and robustness of the proposed approach are substantiated by experimental results using a conventional 6R industrial manipulator (KUKA KR 6 R900 sixx [AGILUS]) for positioning and tracking tasks.Spanish Government, Grant/Award Number: BES-2010-038486; Generalitat Valenciana, Grant/Award Number: BEST/2017/029 and APOSTD/2016/044Muñoz-Benavent, P.; Gracia, L.; Solanes, JE.; Esparza, A.; Tornero, J. (2018). Sliding mode control for robust and smooth reference tracking in robot visual servoing. International Journal of Robust and Nonlinear Control. 28(5):1728-1756. https://doi.org/10.1002/rnc.3981S17281756285Hutchinson, S., Hager, G. D., & Corke, P. I. (1996). A tutorial on visual servo control. IEEE Transactions on Robotics and Automation, 12(5), 651-670. doi:10.1109/70.538972Chaumette, F., & Hutchinson, S. (2008). Visual Servoing and Visual Tracking. Springer Handbook of Robotics, 563-583. doi:10.1007/978-3-540-30301-5_25Corke, P. (2011). Robotics, Vision and Control. Springer Tracts in Advanced Robotics. doi:10.1007/978-3-642-20144-8RYAN, E. P., & CORLESS, M. (1984). Ultimate Boundedness and Asymptotic Stability of a Class of Uncertain Dynamical Systems via Continuous and Discontinuous Feedback Control. IMA Journal of Mathematical Control and Information, 1(3), 223-242. doi:10.1093/imamci/1.3.223Chaumette, F., & Hutchinson, S. (2006). Visual servo control. I. Basic approaches. IEEE Robotics & Automation Magazine, 13(4), 82-90. doi:10.1109/mra.2006.250573Chaumette, F., & Hutchinson, S. (2007). Visual servo control. II. Advanced approaches [Tutorial]. IEEE Robotics & Automation Magazine, 14(1), 109-118. doi:10.1109/mra.2007.339609Bonfe M Mainardi E Fantuzzi C Variable structure PID based visual servoing for robotic tracking and manipulation 2002 Lausanne, Switzerland https://doi.org/10.1109/IRDS.2002.1041421Solanes, J. E., Muñoz-Benavent, P., Girbés, V., Armesto, L., & Tornero, J. (2015). On improving robot image-based visual servoing based on dual-rate reference filtering control strategy. Robotica, 34(12), 2842-2859. doi:10.1017/s0263574715000454Elena M Cristiano M Damiano F Bonfe M Variable structure PID controller for cooperative eye-in-hand/eye-to-hand visual servoing 2003 Istanbul, Turkey https://doi.org/10.1109/CCA.2003.1223145Hashimoto, K., Ebine, T., & Kimura, H. (1996). Visual servoing with hand-eye manipulator-optimal control approach. IEEE Transactions on Robotics and Automation, 12(5), 766-774. doi:10.1109/70.538981Chan A Leonard S Croft EA Little JJ Collision-free visual servoing of an eye-in-hand manipulator via constraint-aware planning and control 2011 San Francisco, CA, USA https://doi.org/10.1109/ACC.2011.5991008Allibert, G., Courtial, E., & Chaumette, F. (2010). Visual Servoing via Nonlinear Predictive Control. Lecture Notes in Control and Information Sciences, 375-393. doi:10.1007/978-1-84996-089-2_20Kragic, D., & Christensen, H. I. (2003). Robust Visual Servoing. The International Journal of Robotics Research, 22(10-11), 923-939. doi:10.1177/027836490302210009Mezouar Y Chaumette F Path planning in image space for robust visual servoing 2000 San Francisco, CA, USA https://doi.org/10.1109/ROBOT.2000.846445Morel, G., Zanne, P., & Plestan, F. (2005). Robust visual servoing: bounding the task function tracking errors. IEEE Transactions on Control Systems Technology, 13(6), 998-1009. doi:10.1109/tcst.2005.857409Hammouda, L., Kaaniche, K., Mekki, H., & Chtourou, M. (2015). Robust visual servoing using global features based on random process. International Journal of Computational Vision and Robotics, 5(2), 138. doi:10.1504/ijcvr.2015.068803Yang YX Liu D Liu H Robot-self-learning visual servoing algorithm using neural networks 2002 Beijing, China https://doi.org/10.1109/ICMLC.2002.1174473Sadeghzadeh, M., Calvert, D., & Abdullah, H. A. (2014). Self-Learning Visual Servoing of Robot Manipulator Using Explanation-Based Fuzzy Neural Networks and Q-Learning. Journal of Intelligent & Robotic Systems, 78(1), 83-104. doi:10.1007/s10846-014-0151-5Lee AX Levine S Abbeel P Learning Visual Servoing With Deep Features and Fitted Q-Iteration 2017Fakhry, H. H., & Wilson, W. J. (1996). A modified resolved acceleration controller for position-based visual servoing. Mathematical and Computer Modelling, 24(5-6), 1-9. doi:10.1016/0895-7177(96)00112-4Keshmiri, M., Wen-Fang Xie, & Mohebbi, A. (2014). Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command. IEEE Transactions on Industrial Electronics, 61(10), 5444-5452. doi:10.1109/tie.2014.2300048Edwards, C., & Spurgeon, S. (1998). Sliding Mode Control. doi:10.1201/9781498701822Zanne P Morel G Piestan F Robust vision based 3D trajectory tracking using sliding mode control 2000 San Francisco, CA, USAOliveira TR Peixoto AJ Leite AC Hsu L Sliding mode control of uncertain multivariable nonlinear systems applied to uncalibrated robotics visual servoing 2009 St. Louis, MO, USAOliveira, T. R., Leite, A. C., Peixoto, A. J., & Hsu, L. (2014). Overcoming Limitations of Uncalibrated Robotics Visual Servoing by means of Sliding Mode Control and Switching Monitoring Scheme. Asian Journal of Control, 16(3), 752-764. doi:10.1002/asjc.899Li, F., & Xie, H.-L. (2010). Sliding mode variable structure control for visual servoing system. International Journal of Automation and Computing, 7(3), 317-323. doi:10.1007/s11633-010-0509-5Kim J Kim D Choi S Won S Image-based visual servoing using sliding mode control 2006 Busan, South KoreaBurger W Dean-Leon E Cheng G Robust second order sliding mode control for 6D position based visual servoing with a redundant mobile manipulator 2015 Seoul, South KoreaBecerra, H. M., López-Nicolás, G., & Sagüés, C. (2011). A Sliding-Mode-Control Law for Mobile Robots Based on Epipolar Visual Servoing From Three Views. IEEE Transactions on Robotics, 27(1), 175-183. doi:10.1109/tro.2010.2091750Parsapour, M., & Taghirad, H. D. (2015). Kernel-based sliding mode control for visual servoing system. IET Computer Vision, 9(3), 309-320. doi:10.1049/iet-cvi.2013.0310Xin J Ran BJ Ma XM Robot visual sliding mode servoing using SIFT features 2016 Chengdu, ChinaZhao, Y. M., Lin, Y., Xi, F., Guo, S., & Ouyang, P. (2016). Switch-Based Sliding Mode Control for Position-Based Visual Servoing of Robotic Riveting System. Journal of Manufacturing Science and Engineering, 139(4). doi:10.1115/1.4034681Moosavian, S. A. A., & Papadopoulos, E. (2007). Modified transpose Jacobian control of robotic systems. Automatica, 43(7), 1226-1233. doi:10.1016/j.automatica.2006.12.029Sagara, S., & Taira, Y. (2008). Digital control of space robot manipulators with velocity type joint controller using transpose of generalized Jacobian matrix. Artificial Life and Robotics, 13(1), 355-358. doi:10.1007/s10015-008-0584-7Khalaji, A. K., & Moosavian, S. A. A. (2015). Modified transpose Jacobian control of a tractor-trailer wheeled robot. Journal of Mechanical Science and Technology, 29(9), 3961-3969. doi:10.1007/s12206-015-0841-3Utkin, V., Guldner, J., & Shi, J. (2017). Sliding Mode Control in Electro-Mechanical Systems. doi:10.1201/9781420065619Utkin, V. (2016). Discussion Aspects of High-Order Sliding Mode Control. IEEE Transactions on Automatic Control, 61(3), 829-833. doi:10.1109/tac.2015.2450571Romdhane, H., Dehri, K., & Nouri, A. S. (2016). Discrete second-order sliding mode control based on optimal sliding function vector for multivariable systems with input-output representation. International Journal of Robust and Nonlinear Control, 26(17), 3806-3830. doi:10.1002/rnc.3536Sharma, N. K., & Janardhanan, S. (2017). Optimal discrete higher-order sliding mode control of uncertain LTI systems with partial state information. International Journal of Robust and Nonlinear Control. doi:10.1002/rnc.3785LEVANT, A. (1993). Sliding order and sliding accuracy in sliding mode control. International Journal of Control, 58(6), 1247-1263. doi:10.1080/00207179308923053Levant, A. (2003). Higher-order sliding modes, differentiation and output-feedback control. International Journal of Control, 76(9-10), 924-941. doi:10.1080/0020717031000099029Bartolini, G., Ferrara, A., & Usai, E. (1998). Chattering avoidance by second-order sliding mode control. IEEE Transactions on Automatic Control, 43(2), 241-246. doi:10.1109/9.661074Siciliano, B., Sciavicco, L., Villani, L., & Oriolo, G. (2009). Robotics. Advanced Textbooks in Control and Signal Processing. doi:10.1007/978-1-84628-642-1Deo, A. S., & Walker, I. D. (1995). Overview of damped least-squares methods for inverse kinematics of robot manipulators. Journal of Intelligent & Robotic Systems, 14(1), 43-68. doi:10.1007/bf01254007WHEELER, G., SU, C.-Y., & STEPANENKO, Y. (1998). A Sliding Mode Controller with Improved Adaptation Laws for the Upper Bounds on the Norm of Uncertainties. Automatica, 34(12), 1657-1661. doi:10.1016/s0005-1098(98)80024-1Yu-Sheng Lu. (2009). Sliding-Mode Disturbance Observer With Switching-Gain Adaptation and Its Application to Optical Disk Drives. IEEE Transactions on Industrial Electronics, 56(9), 3743-3750. doi:10.1109/tie.2009.2025719Chen, X., Shen, W., Cao, Z., & Kapoor, A. (2014). A novel approach for state of charge estimation based on adaptive switching gain sliding mode observer in electric vehicles. Journal of Power Sources, 246, 667-678. doi:10.1016/j.jpowsour.2013.08.039Cong, B. L., Chen, Z., & Liu, X. D. (2012). On adaptive sliding mode control without switching gain overestimation. International Journal of Robust and Nonlinear Control, 24(3), 515-531. doi:10.1002/rnc.2902Taleb, M., Plestan, F., & Bououlid, B. (2014). An adaptive solution for robust control based on integral high-order sliding mode concept. International Journal of Robust and Nonlinear Control, 25(8), 1201-1213. doi:10.1002/rnc.3135Zhu, J., & Khayati, K. (2016). On a new adaptive sliding mode control for MIMO nonlinear systems with uncertainties of unknown bounds. International Journal of Robust and Nonlinear Control, 27(6), 942-962. doi:10.1002/rnc.3608Hafez AHA Cervera E Jawahar CV Hybrid visual servoing by boosting IBVS and PBVS 2008 Damascus, SyriaKermorgant O Chaumette F Combining IBVS and PBVS to ensure the visibility constraint 2011 San Francisco, CA, USACorke, P. I., & Hutchinson, S. A. (2001). A new partitioned approach to image-based visual servo control. IEEE Transactions on Robotics and Automation, 17(4), 507-515. doi:10.1109/70.954764Yang, Z., & Shen, S. (2017). Monocular Visual–Inertial State Estimation With Online Initialization and Camera–IMU Extrinsic Calibration. IEEE Transactions on Automation Science and Engineering, 14(1), 39-51. doi:10.1109/tase.2016.2550621Chesi G Hashimoto K Static-eye against hand-eye visual servoing 2002 Las Vegas, NV, USABourdis N Marraud D Sahbi H Camera pose estimation using visual servoing for aerial video change detection 2012 Munich, GermanyShademan A Janabi-Sharifi F Sensitivity analysis of EKF and iterated EKF pose estimation for position-based visual servoing 2005 USAMalis, E., Mezouar, Y., & Rives, P. (2010). Robustness of Image-Based Visual Servoing With a Calibrated Camera in the Presence of Uncertainties in the Three-Dimensional Structure. IEEE Transactions on Robotics, 26(1), 112-120. doi:10.1109/tro.2009.2033332Chen J Behal A Dawson D Dixon W Adaptive visual servoing in the presence of intrinsic calibration uncertainty 2003 USAMezouar Y Malis E Robustness of central catadioptric image-based visual servoing to uncertainties on 3D parameters 2004 Sendai, JapanMarchand, E., Spindler, F., & Chaumette, F. (2005). ViSP for visual servoing: a generic software platform with a wide class of robot control skills. IEEE Robotics & Automation Magazine, 12(4), 40-52. doi:10.1109/mra.2005.157702

The cost of space independence in P300-BCI spellers.

Background: Though non-invasive EEG-based Brain Computer Interfaces (BCI) have been researched extensively over the last two decades, most designs require control of spatial attention and/or gaze on the part of the user. Methods: In healthy adults, we compared the offline performance of a space-independent P300-based BCI for spelling words using Rapid Serial Visual Presentation (RSVP), to the well-known space-dependent Matrix P300 speller. Results: EEG classifiability with the RSVP speller was as good as with the Matrix speller. While the Matrix speller’s performance was significantly reliant on early, gaze-dependent Visual Evoked Potentials (VEPs), the RSVP speller depended only on the space-independent P300b. However, there was a cost to true spatial independence: the RSVP speller was less efficient in terms of spelling speed. Conclusions: The advantage of space independence in the RSVP speller was concomitant with a marked reduction in spelling efficiency. Nevertheless, with key improvements to the RSVP design, truly space-independent BCIs could approach efficiencies on par with the Matrix speller. With sufficiently high letter spelling rates fused with predictive language modelling, they would be viable for potential applications with patients unable to direct overt visual gaze or covert attentional focus