TY - Generic T1 - Interaction control for rehabilitation robotics via a low-cost force sensing handle T2 - 6th Annual ASME Dynamic Systems and Controls Conference Y1 - 2013 A1 - Andrew Erwin A1 - Fabrizio Sergi A1 - Vinay Chawda A1 - Marcia K. O'Malley JF - 6th Annual ASME Dynamic Systems and Controls Conference CY - Palo Alto, CA ER - TY - Generic T1 - A Method for Selecting Velocity Filter Cutoff Frequency for Maximizing Impedance Width Performance in Haptic Interfaces T2 - 6th Annual ASME Dynamic Systems and Controls Conference Y1 - 2013 A1 - Vinay Chawda A1 - Ozkan Celik A1 - Marcia K. O'Malley JF - 6th Annual ASME Dynamic Systems and Controls Conference CY - Palo Alto, CA ER - TY - Generic T1 - On the Performance of Passivity-based Control of Haptic Displays Employing Levant's Differentiator for Velocity Estimation T2 - IEEE Haptics Symposium Y1 - 2012 A1 - Vinay Chawda A1 - Marcia K. O'Malley AB -

In impedance-type haptic interfaces, encoders are typically employed to provide high resolution position measurements from which velocity is estimated, most commonly via the finite difference method (FDM). This velocity estimation technique performs reliably, unless very fast sampling is required, in which case noise or delay due to filtering of the position signals reduces accuracy in the estimate. Despite this limitation, FDM is attractive because it is a passive process, and therefore the passivity of the overall system can be guaranteed. Levant's differentiator is a viable alternative to FDM, and exhibits increased accuracy in velocity estimation at high sample rates compared to FDM. However, the passivity of this nonlinear velocity estimation technique cannot be shown using conventional methods. In this paper, we employ a time domain passivity framework to analyze and enforce passive behavior of Levant's differentiator for haptic displays in discrete time. The performance of this approach is explored both in simulation and experimentally on a custom made one degree-of-freedom haptic interface. Results demonstrate the effectiveness of the time domain passivity approach for compensating the active behavior observed with use of Levant's differentiator for velocity estimation.

JF - IEEE Haptics Symposium PB - IEEE CY - Vancouver, BC, Canada SN - 978-1-4673-0808-3 ER - TY - Generic T1 - Application of Levant’s Differentiator for Velocity Estimation and Increased Z-Width in Haptic Interfaces T2 - IEEE World Haptics Conference 2011 Y1 - 2011 A1 - Vinay Chawda A1 - Ozkan Celik A1 - Marcia K. O'Malley JF - IEEE World Haptics Conference 2011 PB - IEEE CY - Istanbul, Turkey ER - TY - Generic T1 - A Lyapunov Approach for SOSM Based Velocity Estimation and its Application to Improve Bilateral Teleoperation Performance T2 - Proceedings of the ASME 2011 Dynamic Systems and Control Conference Y1 - 2011 A1 - Vinay Chawda A1 - Marcia K. O'Malley JF - Proceedings of the ASME 2011 Dynamic Systems and Control Conference ER - TY - JOUR T1 - Vision-Based Force Sensing for Nanomanipulation JF - IEEE /ASME Transactions on Mechatronics Y1 - 2011 A1 - Vinay Chawda A1 - O'Malley, M.K. AB - A vision-based algorithm for estimating tip interaction forces on a deflected Atomic Force Microscope (AFM) cantilever is described. Specifically, we propose that the algorithm can estimate forces acting on an Atomic Force Microscope (AFM) cantilever being used as a nanomanipulator inside a Scanning Electron Microscope (SEM). The vision based force sensor can provide force feedback in real-time, a feature absent in many SEMs. A methodology based on cantilever slope detection is used to estimate the forces acting on the cantilever tip. The technique was tested on a scaled model of the nanoscale AFM cantilever and verified using theoretical estimates as well as direct strain measurements. Artificial SEM noise was introduced in the macroscale images to characterize our sensor under varying levels of noise and other SEM effects. Prior knowledge about the cantilever is not required, and the algorithm runs independent of human input. The method is shown to be effective under varying noise levels, and demonstrates improving performance as magnification levels are decreased. Therefore, we conclude that the vision-based force sensing algorithm is best suited for continuous operation of the SEM, fast scanning rates, and large fields-of-view associated with low magnification levels. UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5692832 ER -