Elevating haptic interfaces: Dual-rate sampling and field programmable gate array implementation for multi-degree-of-freedom performance enhancement

Majid Koul, Suhail Khosa, Babar Ahmad

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International Journal of Mechanical System Dynamics ›› 2024, Vol. 4 ›› Issue (2) : 171-187. DOI: 10.1002/msd2.12115
RESEARCH ARTICLE

Elevating haptic interfaces: Dual-rate sampling and field programmable gate array implementation for multi-degree-of-freedom performance enhancement

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Abstract

In this work, our primary focus centered on exploring the adaptability of the dualrate sampling scheme proposed earlier to enhance the performance of multi-degree-of-freedom (multi-DOF) impedance-based haptic interfaces. The scheme employed independent sampling rates in a haptics controller, effectively mitigating the issue of reduced Z-width at higher sampling rates. A key aspect of our investigation was the intricate implementation of the dual-rate sampling scheme on a field programmable gate array (FPGA). This implementation on a logic hardware FPGA was challenging and led to the effective comparison of the uniform-rate and dual-rate sampling schemes of the multi-DOF haptic controller. We used an in-house developed two-DOF pantograph as the haptic interface and an FPGA for implementing the controller strategy. FPGA-based implementation presented challenges that were vital in testing controller performances at higher sampling rates. Virtual wall experiments were conducted to determine the stable and unstable interactions with the virtual wall. To complement the experimental results, we simulated the haptics force law for multi-DOF system on Simulink/MATLAB. Notably, the dual-rate sampling approach maintained the Z-width of the two-DOF haptic interface, even at higher controller sampling rates, distinguishing it from the conventional two-DOF uniform-rate control scheme. For example, employing a dual-rate sampling combination of 20–2 kHz consistently ensured the stable rendering of a maximum virtual stiffness of approximately 700 N/mm and maintained a reliable virtual damping range spanning from 0 to 5 Ns/mm. In contrast, the 20 kHz uniform-rate sampling approach failed to ensure interface stability in the presence of virtual damping, ultimately resulting in the unsuccessful implementation of any virtual stiffness at higher sampling rates. This work, therefore, establishes the potential of dual-rate sampling in the realm of haptic technology, with practical applications in multi-DOF systems.

Keywords

control FPGA / haptic device / simulation virtual reality / Z-width

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Majid Koul, Suhail Khosa, Babar Ahmad. Elevating haptic interfaces: Dual-rate sampling and field programmable gate array implementation for multi-degree-of-freedom performance enhancement. International Journal of Mechanical System Dynamics, 2024, 4(2): 171‒187 https://doi.org/10.1002/msd2.12115

References

[1]
Gibbs JK, Gillies M, Pan X. A comparison of the effects of haptic and visual feedback on presence in virtual reality. Int J Hum Comput Stud. 2022;157:102717.
CrossRef Google scholar
[2]
Cutlip S, Wan Y, Sarter N, Gillespie RB. The effects of haptic feedback and transition type on transfer of control between drivers and vehicle automation. IEEE T Hum-Mach Syst. 2021;51(6):613-621.
CrossRef Google scholar
[3]
Tholey G, Desai JP, Castellanos AE. Force feedback plays a significant role in minimally invasive surgery: results and analysis. Ann Surg. 2005;241(1):102-109.
CrossRef Google scholar
[4]
Pacchierotti C, Prattichizzo D, Kuchenbecker KJ. Cutaneous feedback of fingertip deformation and vibration for palpation in robotic surgery. IEEE Trans Biomed Eng. 2016;63(2):278-287.
CrossRef Google scholar
[5]
Miller J, Braun M, Bilz J, et al. Impact of haptic feedback on applied intracorporeal forces using a novel surgical robotic system—a randomized cross-over study with novices in an experimental setup. Surg Endosc. 2021;35:3554-3563.
CrossRef Google scholar
[6]
Culbertson H, Schorr SB, Okamura AM. Haptics: the present and future of artificial touch sensation. Annu Rev Control Robot Auton Syst. 2018;1:385-409.
CrossRef Google scholar
[7]
Dangxiao W, Yuan G, Shiyi L, Zhang Y, Weiliang X, Jing X. Haptic display for virtual reality: progress and challenges. Virtual Real Intell Hardw. 2019;1(2):136-162.
CrossRef Google scholar
[8]
Giri GS, Maddahi Y, Zareinia K. An application-based review of haptics technology. Robotics. 2021;10(1):29.
CrossRef Google scholar
[9]
Forsslund J, Chan S, Selesnick J, Salisbury K, Silva RG, Blevins NH. The effect of haptic degrees of freedom on task performance in virtual surgical environments. Stud Health Technol Inform. 2013;184:129-135.
[10]
Gil JJ, Avello A, Rubio A, Florez J. Stability analysis of a 1 DOF haptic interface using the routh-hurwitz criterion. IEEE Trans Control Syst Technol. 2004;12(4):583-588.
CrossRef Google scholar
[11]
Abbott JJ, Okamura AM. Effects of position quantization and sampling rate on virtual-wall passivity. IEEE Trans Robot. 2005;21(5):952-964.
CrossRef Google scholar
[12]
Orta Martinez M, Nunez CM, Liao T, Morimoto TK, Okamura AM. Evolution and analysis of hapkit: an open-source haptic device for educational applications. IEEE Trans Haptics. 2020;13(2):354-367.
CrossRef Google scholar
[13]
Gonenc B, Gurocak H. Virtual tissue cutting with haptic feedback using a hybrid actuator with DC servomotor and magnetorheological brake. J Comput Inf Sci Eng. 2016;16(3):030902.
CrossRef Google scholar
[14]
McNeely WA, Puterbaugh KD, Troy JJ. Six degree-of-freedom haptic rendering using voxel sampling. In: Fujii J, ed. SIGGRAPH ’99. ACM Press/Addison-Wesley Publishing Co;1999:401-408.
[15]
Basdogan C, Laycock S, Day A, Patoglu V, Gillespie R. 3-DOF haptic rendering. Haptic rendering. 2007.
[16]
Ramstein C, Hayward V. The pantograph: a large workspace haptic device for multimodal human computer interaction. In: Plaisant C, ed. CHI ’94 Association for Computing Machinery. Association for Computing Machinery;1994:57-58.
[17]
Gallacher C, Mohtat A, Ding S, Kövecses J. Toward open-source portable haptic displays with visual-force-tactile feedback colocation. 2016 IEEE Haptics Symposium (HAPTICS). IEEE;2016:65-71.
CrossRef Google scholar
[18]
Tsai MD, Hsieh MS, Tsai CH. Bone drilling haptic interaction for orthopedic surgical simulator. Comput Biol Med. 2007;37(12):1709-1718.
CrossRef Google scholar
[19]
Wang D, Zhang Y, Hou J, et al. iDental: a haptic-based dental simulator and its preliminary user evaluation. IEEE Trans Haptics. 2012;5(4):332-343.
CrossRef Google scholar
[20]
Colgate JE, Brown JM. Factors affecting the z-width of a haptic display. Proceedings of the 1994 IEEE International Conference on Robotics and Automation. IEEE;1994:3205-3210.
[21]
Gillespie RB, Cutkosky MR. table user-specific haptic rendering of the virtual wall. Proceedings of the ASME International Mechanical Engineering Congress and Exhibition. Vol 58, ASME;1996:397-406.
[22]
Diolaiti N, Niemeyer G, Barbagli F, Salisbury JK. Stability of haptic rendering: discretization, quantization, time delay, and Coulomb effects. IEEE Trans Robot. 2006;22(2):256-268.
CrossRef Google scholar
[23]
Gil JJ, Sánchez E, Hulin T, Preusche C, Hirzinger G. Stability boundary for haptic rendering: influence of damping and delay. J Comput Inf Sci Eng. 2009;9(1):011005.
CrossRef Google scholar
[24]
Mashayekhi A, Behbahani S, Ficuciello F, Siciliano B. Analytical stability criterion in haptic rendering: the role of damping. IEEE/ASME Trans Mechatron. 2018;23(2):596-603.
CrossRef Google scholar
[25]
Mehling JS, Colgate JE, Peshkin MA. Increasing the impedance range of a haptic display by adding electrical damping. First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics. IEEE;2005:257-262.
[26]
Weir DW, Colgate JE, Peshkin MA. Measuring and increasing Z-width with active electrical damping. Symposium on Haptic interfaces for virtual environment and teleoperator systems. Haptics. 2008;IEEE;2008:169-175.
[27]
Gosline AHC, Hayward V. Eddy current brakes for haptic interfaces: design, identification, and control. IEEE/ASME Trans Mechatron. 2008;13(6):669-677.
CrossRef Google scholar
[28]
Srikanth MB, Vasudevan H, Muniyandi M. DC motor damping: a strategy to increase passive stiffness of haptic devices. International Conference on Human Haptic Sensing and Touch Enabled Computer Applications. Springer;2008:53-62.
CrossRef Google scholar
[29]
Lim YA, Ahn HS, Ryu J. Analogue input shaper for haptic interfaces. IET Control Theory Appl. 2009;3(12):1553-1564.
CrossRef Google scholar
[30]
O’Malley MK, Sevcik KS, Kopp E. Improved haptic fidelity via reduced sampling period with an FPGA-based real-time hardware platform. J Comput Inf Sci Eng. 2009;9(1):011002.
CrossRef Google scholar
[31]
Chawda V, Celik O, O’Malley MK. A method for selecting velocity filter cut-off frequency for maximizing impedance width performance in haptic interfaces. J Dyn Syst Meas Control. 2015;137(2):024503.
CrossRef Google scholar
[32]
Colonnese N, Okamura A. Stability and quantization-error analysis of haptic rendering of virtual stiffness and damping. Int J Robot Res. 2016;35(9):1103-1120.
CrossRef Google scholar
[33]
Janabi-Sharifi F, Hayward V, Chen CSJ. Discrete-time adaptive windowing for velocity estimation. IEEE Trans Control Syst Technol. 2000;8(6):1003-1009.
CrossRef Google scholar
[34]
Chawda V, Celik O, O’Malley MK. Application of Levant’s differentiator for velocity estimation and increased z-width in haptic interfaces. World Haptics Conference (WHC). IEEE;2011:403-408.
[35]
Ghaffari TK, Kövecses J. A high-performance velocity estimator for haptic applications. World Haptics Conference (WHC). IEEE;2013:127-132.
[36]
Chu R, Zhang Y, Zhang H, Xu W, Ryu JH, Wang D. Co-actuation: a method for achieving high stiffness and low inertia for haptic devices. IEEE Trans Haptics 2020;13(2):312-324.
CrossRef Google scholar
[37]
Wang Y, Feng L, Andersson K. A position-control based approach to haptic rendering of stiff objects. IEEE Trans Haptics. 2021;14(3):646-659.
CrossRef Google scholar
[38]
Wang Y, Feng L, Andersson K. A position control-based approach to haptic rendering of stiff objects using piece-wise linear model. Adv Mech Eng. 2021;13(12):168781402110648.
CrossRef Google scholar
[39]
Wang Y, Feng L, Andersson K. A joint-space position control-based approach to haptic rendering of stiff objects using gain scheduling. J Intell Robot Syst. 2021;103:1-15.
CrossRef Google scholar
[40]
Yin X, Wu C, Wen S, Zhang J. Smart design of Z-width expanded thumb haptic interface using magnetorheological fluids. IEEE Trans Instrum Meas. 2021;70:1-11.
CrossRef Google scholar
[41]
Choi H, Kim NG, Jafari A, Singh H, Ryu JH. Virtual inertia as an energy dissipation element for haptic interfaces. IEEE Robot Autom Lett. 2022;7(2):2708-2715.
CrossRef Google scholar
[42]
Carignan CR, Cleary KR. Closed-loop force control for haptic simulation of virtual environments. 2000.
[43]
Lee K, Lee DY. Multirate control of haptic interface for stability and high fidelity. 2004 IEEE International Conference Systems, Man and Cybernetics. Vol 3. IEEE;2004:2542-2547.
[44]
Koul M, Manivannan M, Saha S. Effect of dual-rate sampling on the stability of a haptic interface. J Intell Robot Syst. 2017;91:479-491.
CrossRef Google scholar
[45]
Kim M, Lee DY. Multirate haptic rendering using local stiffness matrix for stable and transparent simulation involving interaction with deformable objects. IEEE Trans Ind Electron. 2020;67(1):820-828.
CrossRef Google scholar
[46]
Mahvash M, Hayward V. Haptic rendering—beyond visual computing—high-fidelity haptic synthesis of contact with deformable bodies. IEEE Comput Graph Appl. 2004;24(2):48-55.
CrossRef Google scholar
[47]
Ganiny S, Koul MH, Ahmad B. Time-delayed dual-rate haptic rendering: stability analysis and reduced order modeling. Int J Intell Robotics Appl. 2021;5(4):510-533.
CrossRef Google scholar
[48]
Ganiny S, Koul MH, Ahmad B. Identification of the most conservative stability bounds for a class of multi-rate haptics controllers. Int J Model, Identif Control. 2022;41(4):357-374.
CrossRef Google scholar
[49]
Ganiny S, Koul MH, Ahmad B. Analysis of limit cycle oscillations in dual-rate haptic rendering: effect of dual-rate sampling. IFACPapersOnLine. 2022;55(1):655-660.
CrossRef Google scholar
[50]
Jafari A, Ryu JH. 6-DOF extension of memory-based passivation approach for stable haptic interaction. Intell Serv Robot. 2015;8:23-34.
CrossRef Google scholar
[51]
Desai I, Gupta A, Chakraborty D. Rendering stiff virtual walls using model matching based haptic controller. IEEE Trans Haptics. 2019.
[52]
Shayan-Amin S, Kovács LL, Kövecses J. The role of mechanical properties on the behaviour and performance of multi-DOF haptic devices. World Haptics Conference (WHC). IEEE;2013:725-730.
CrossRef Google scholar
[53]
Koul M, Rabinowitz D, Saha S, Manivannan M. Synthesis and design of a 2-DOF haptic device for simulating epidural injection. Proceedings 13th World Congress in Mechanism and Machine Science, Guanajuato, Mexico, 19-23 June 2011. Member Organisation Mexico of IFToMM; 2011;1–7.
[54]
Łącki M, DeBoon B, Rossa C. Impact of kinematic structure on the force displayability of planar passive haptic devices. IEEE Trans Haptics. 2020;13(1):219-225.
CrossRef Google scholar
[55]
Yoshikawa T. Manipulability of robotic mechanisms. Int J Robot Res. 1985;4(2):3-9.
CrossRef Google scholar
[56]
Gil JJ, Diaz I. Haptic performance using Voltage-Mode motor control. IEEE Trans Ind Electron. 2020;67:698-705.
CrossRef Google scholar
[57]
Smith SW. The Scientist and Engineer’s Guide to Digital Signal Processing, 1997:67-86.
[58]
Volder JE. The CORDIC trigonometric computing technique. IRE Trans Electron Comput. 1959;EC-8(3):330-334.
CrossRef Google scholar
[59]
Vachhani L, Sridharan K, Meher PK. Efficient CORDIC algorithms and architectures for low area and high throughput implementation. IEEE Trans Circuits Syst II Express Briefs. 2009;56(1):61-65.
CrossRef Google scholar
[60]
Vladimirova T, Tiggeler H. FPGA implementation of sine and cosine generators using the CORDIC algorithm. Proceedings of Military and Aerospace Application of Programmable Devices and Technologies Conference (MAPLD 99), 1999:28-30.
[61]
Koul MH, Saha SK, Manivannan M. Simulation of haptics force law using simmechanics and Simulink. Proceedings of the 1st International and 16th National Conference on Machines and Mechanisms (iNaCoMM2013), Roorkee, Uttar Pradesh, India, 18-20 December 2013. IIT Roorkee;2013.

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