Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-10T20:17:43.156Z Has data issue: false hasContentIssue false
  • English
  • Français

Effects of Dynamic Model Errors in Task-Priority Operational Space Control

Published online by Cambridge University Press:  01 February 2021

Paolo Di Lillo Open the ORCID record for Paolo Di Lillo [Opens in a new window] ,
Gianluca Antonelli  and
Ciro Natale
Paolo Di Lillo*
Affiliation:
Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy. E-mail: antonelli@unicas.it
Gianluca Antonelli
Affiliation:
Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, Cassino, Italy. E-mail: antonelli@unicas.it
Ciro Natale
Affiliation:
Dipartimento di Ingegneria, Università degli Studi della Campania “Luigi Vanvitelli”, Aversa, Italy. E-mail: ciro.natale@unicampania.it
*
*Corresponding author. E-mail: pa.dilillo@unicas.it
Get access Rights & Permissions [Opens in a new window]

Summary

Control algorithms of many Degrees-of-Freedom (DOFs) systems based on Inverse Kinematics (IK) or Inverse Dynamics (ID) approaches are two well-known topics of research in robotics. The large number of DOFs allows the design of many concurrent tasks arranged in priorities, that can be solved either at kinematic or dynamic level. This paper investigates the effects of modeling errors in operational space control algorithms with respect to uncertainties affecting knowledge of the dynamic parameters. The effects on the null-space projections and the sources of steady-state errors are investigated. Numerical simulations with on-purpose injected errors are used to validate the thoughts.

Keywords

Task-priority controlOperational space controlModel uncertainties
Type
Article
Information
Robotica , Volume 39 , Issue 9 , September 2021 , pp. 1642 - 1653
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antonelli, G., “Stability analysis for prioritized closed-loop inverse kinematic algorithms for redundant robotic systems,” IEEE Trans. Robot. 25(5), 985–994 (2009).CrossRefGoogle Scholar
Antonelli, G., Di Lillo, P. and Natale, C., “Modeling Errors Analysis in Inverse Dynamics Approaches within a Task-Priority Framework,” 2018 IEEE Conference on Control Technology and Applications, Copenhagen, Denmark (2018) pp. 553–558.CrossRefGoogle Scholar
Bjerkeng, M., Falco, P., Natale, C. and Pettersen, K. Y., “Discrete-Time Stability Analysis of a Control Architecture for Heterogeneous Robotic Systems,” Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo (2013) pp. 4778–4783.CrossRefGoogle Scholar
Bjerkeng, M., Falco, P., Natale, C. and Pettersen, K. Y., “Stability analysis of a hierarchical architecture for discrete-time sensor-based control of robotic systems,” IEEE Trans. Robot. 30(3), 745–753 (2014).CrossRefGoogle Scholar
Dietrich, A. and Ott, C., “Hierarchical impedance-based tracking control of kinematically redundant robots,” IEEE Trans. Robot. 36(1), 204–221 (2020).CrossRefGoogle Scholar
Dietrich, A., Ott, C. and Park, J., “The hierarchical operational space formulation: Stability analysis for the regulation case,” IEEE Robot. Autom. Lett. 3(2), 1120–1127 (2018).CrossRefGoogle Scholar
Khatib, O., “A unified approach for motion and force control of robot manipulators: The operational space formulation,” IEEE J. Robot. Autom. 3(1), 43–53 (1987).CrossRefGoogle Scholar
Khatib, O., Sentis, L., Park, J. and Warren, J., “Whole-body dynamic behavior and control of human-like robots,” Int. J. Humanoid Robot. 1(1), 29–43 (2004).CrossRefGoogle Scholar
Lee, J., Chang, P. H. and Jamisola, R. S., “Relative Task Prioritization for Dual-Arm with Multiple, Conflicting Tasks: Derivation and Experiments,” 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany (IEEE, 2013) pp. 1928–1933.CrossRefGoogle Scholar
Moe, S., Antonelli, G., Teel, A., Pettersen, K. and Schrimpf, J., “Set-based tasks within the singularity-robust multiple task-priority inverse kinematics framework: General formulation, stability analysis and experimental results,” Front. Robot. AI 3, 16 (2016).CrossRefGoogle Scholar
Moe, S., Teel, A., Antonelli, G. and Pettersen, K., “Stability Analysis for Set-Based Control within the Singularity-Robust Multiple Task-Priority Inverse Kinematics Framework,” 54th IEEE Conference on Decision and Control and 8th European Control Conference, Osaka, Japan (2015) pp. 171–178.Google Scholar
Nakanishi, J., Cory, R., Mistry, M., Peters, J. and Schaal, S., “Comparative Experiments on Task Space Control with Redundancy Resolution,” Proceedings 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonton, CA (2005) pp. 3901–3908.CrossRefGoogle Scholar
Nakanishi, J., Cory, R., Mistry, M., Peters, J. and Schaal, S., “Operational space control: A theoretical and empirical comparison,” Int. J. Robot. Res. 27(6), 737–757 (2008).CrossRefGoogle Scholar
Ott, C., Dietrich, A. and Albu-Schäffer, A., “Prioritized multi-task compliance control of redundant manipulators,” Automatica 53(1), 416–423 (2015).CrossRefGoogle Scholar
Peters, J., Mistry, M., Udwadia, F., Nakanishi, J. and Schaal, S., “A unifying methodology for robot control with redundant DOFs,” Auto. Robots 24(1), 1–12 (2008).CrossRefGoogle Scholar
Roy, N., Newman, P. and Srinivasa, S., Experiments with Balancing on Irregular Terrains Using the Dreamer Mobile Humanoid Robot (MITP, 2013).CrossRefGoogle Scholar
Sadeghian, H., Villani, L., Keshmiri, M. and Siciliano, B., “Dynamic multi-priority control in redundant robotic systems,” Robotica 31(7), 1155–1167 (2013).Google Scholar
Sentis, L., Synthesis and Control of Whole-Body Behaviors in Humanoid Systems Ph.D. Thesis (Stanford University, USA, 2007).Google Scholar
Sentis, L. and Khatib, O., “Prioritized Multi-objective Dynamics and Control of Robots in Human Environments,” 2004 4th IEEE/RAS International Conference on Humanoid Robots (2004).Google Scholar
Sentis, L. and Khatib, O., “A Whole-Body Control Framework for Humanoids Operating in Human Environments,” Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006 (IEEE, 2006) pp. 2641–2648.Google Scholar
Sentis, L., Petersen, J. and Philippsen, R., “Implementation and stability analysis of prioritized whole-body compliant controllers on a wheeled humanoid robot in uneven terrains,” Auto. Robots 35(4), 301–319 (2013).CrossRefGoogle Scholar
Siciliano, B., Sciavicco, L., Villani, L. and Oriolo, G., Robotics: Modelling, Planning and Control (Springer Verlag, Germany, 2009).CrossRefGoogle Scholar
Sousa, C. D. and Cortesão, R., “Inertia tensor properties in robot dynamics identification: A linear matrix inequality approach,” IEEE/ASME Trans. Mech. 24(1), 406–411 (2019).CrossRefGoogle Scholar
Valency, T. and Zacksenhouse, M., “Accuracy/robustness dilemma in impedance control,” J. Dyn. Syst. Meas. control 125(3), 310–319 (2003).CrossRefGoogle Scholar