Teleoperation with Haptic Sensor-aided Variable Impedance Control Based on Environment and Human Stiffness Estimation

Zican Wang, Xiao Xu, Dong Yang, Basak Gulecyuz, Fanle Meng, Eckehard Steinbach

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a novel haptic sensor-assisted Variable Impedance Controller (VIC) for the position-force teleoperation architecture, which measures both the environment and human operating stiffness for controller design. The VIC is widely studied and utilized in human-in-the-loop applications to increase control transparency and flexibility. The stiffness adaptation strategy of the traditional VIC estimates human endpoint stiffness during the task demonstrations using wearable Electromyography (EMG) sensors on the operator and utilizes the learned stiffness profile to adjust the controller. The extra sensor complicates scalability for both experimental setups and real-world applications. In this paper, we improve the performance of the teleoperation with VIC, utilizing Learning from Demonstration (LfD) to generate the control strategy with human stiffness. We introduce a human stiffness estimation model that incorporates data from both haptic and robot sensors. This model generates a stiffness profile by employing the Gaussian Mixture Model (GMM) combined with Gaussian Mixture Regression (GMR), ensuring a comprehensive and precise representation of stiffness characteristics. In order to stabilize the system against the energy introduced by time-delayed communication and the VIC, Time Domain Passivity Control (TDPA)-Energy Reflection (ER) is adopted to passivate the control system. For validation, vertical contact experiments with both high- and low-stiffness environments are conducted with or without time delay. The results indicate that our haptic sensor-assisted stiffness profile successfully modifies the controller stiffness to adapt to the environments and the working situation. Also, objective metrics like Rooted Mean Square Error (RMSE) and Peak Signal-Noise Ratio (PSNR) also show that the haptic sensor-assisted VIC improves both the signal feedback quality and the user’s experience compared to traditional constant-stiffness teleoperation controllers.

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Sensors Journal
DOIs
StateAccepted/In press - 2024

Keywords

  • Electromyography
  • Haptic interfaces
  • Manipulators
  • Robot sensing systems
  • Robots
  • Sensors
  • Task analysis
  • haptic technology
  • robotics and automation
  • sensor applications
  • sensor data fusion

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