Haptic Transparency Research Articles

Optimized Sandwich and Topological Structures for Enhanced Haptic Transparency.

Humans rely on multimodal perception to form representations of the world. This implies that environmental stimuli must remain consistent and predictable throughout their journey to our sensory organs. When it comes to vision, electromagnetic waves are minimally affected when passing through air or glass treated for chromatic aberrations. Similar conclusions can be drawn for hearing and acoustic waves. However, tools that propagate elastic waves to our cutaneous afferents tend to color tactual perception due to parasitic mechanical attributes such as resonances and inertia. These issues are often overlooked, despite their critical importance for haptic devices that aim to faithfully render or record tactile interactions. Here, we investigate how to optimize this mechanical transmission with sandwich structures made from rigid, lightweight carbon fiber sheets arranged around a 3D-printed lattice core. Through a comprehensive parametric evaluation, we demonstrate how this design paradigm provides superior haptic transparency, regardless of the lattice types. Drawing an analogy with topology optimization, our solution approaches a foreseeable technological limit. It offers a practical way to create high-fidelity haptic interfaces, opening new avenues for research on tool-mediated interactions.

Optimization-Driven Design of a Kinesthetic Haptic Interface With Human-Like Capabilities.

Developing manipulators for kinesthetic haptic interfaces is challenging due to a large number of design parameters. We propose a novel optimization-driven design approach taking into account the properties of the entire workspace of the human arm instead of a specific task. To achieve this, models of both the human arm and the haptic manipulator are derived and deployed in a suitable objective function, which simultaneously considers poses, velocities, accelerations, as well as displayed forces and torques. A detailed analysis and experiments with real-world motion tracking data show that the proposed method is capable of finding meaningful design parameters to enable good haptic transparency.

Improved Haptic Transparency of Bilateral Control Using Torque-Measured Magnetic Coupling

The integrity and transparency of a haptic feedback in a bilateral control is crucial for precise and accurate operators’ sensation during human–machine interactions. Conventional master and slave bilateral control systems are often subject to unknown or unwanted disturbances and dynamics in the actuators and powertrain linkages that hamper the haptic feedback integrity and transparency. Force sensor torque sensing and feedback control are required to mitigate these effects. In contrast to the conventional approach of introducing torque sensing using a mechanical spring, this paper introduces a magnetic coupling as a torque sensor to detect reaction torque between the human input and the master actuator. Disturbance observer-based torque feedback control is designed to suppress the disturbances and tailor the haptic transparency dynamics. Experimental results on a virtual reality interaction system, which involves the steering wheel bilateral control in a cyber-physical driving simulator system, demonstrate the feasibility and effectiveness of the proposed method with improved haptic integrity and transparency.

Improving Haptic Transparency for Uncertain Virtual Environments Using Adaptive Control and Gain-Scheduled Prediction

The realism or transparency of haptic interfaces is becoming more critical as they are applied to training in fields like minimally invasive surgery (MIS). Surgical training simulators must provide a transparent virtual environment (VE) at a high update rate. Complex, deformable, cuttable tissue models have nonlinear dynamics and are computationally expensive, making it difficult to provide sufficient update rates. The objective of this work is to improve the transparency for this type of VE by formulating the unknown nonlinear dynamics as a quasi-linear parameter varying (LPV) system and designing a predictor to provide an output at a much higher update rate. An adaptive controller based on gain-scheduled prediction is considered for a nonlinear haptic device and a nonlinear, delayed, and sampled VE. The predictor uses feedback from the more accurate but slow-updating VE to update a simplified dynamic model. The predictor is designed based on numerical solutions to a linear matrix inequality derived using Lyapunov-based methods. Experimental results demonstrate the effectiveness of the gain-scheduled predictor approach and compare it to previous work using a constant-gain predictor. The gain-scheduled predictor results in significant performance improvements compared to a haptic system without prediction, but less significant improvement compared to the constant-gain approach.

Haptic Shared Control in Tele-Manipulation: Effects of Inaccuracies in Guidance on Task Execution.

Haptic shared control is a promising approach to improve tele-manipulated task execution, by making safe and effective control actions tangible through guidance forces. In current research, these guidance forces are most often generated based on pre-generated, errorless models of the remote environment. Hence such guidance forces are exempt from the inaccuracies that can be expected in practical implementations. The goal of this research is to quantify the extent to which task execution is degraded by inaccuracies in the model on which haptic guidance forces are based. In a human-in-the-loop experiment, subjects (n = 14) performed a realistic tele-manipulated assembly task in a virtual environment. Operators were provided with various levels of haptic guidance, namely no haptic guidance (conventional tele-manipulation), haptic guidance without inaccuracies, and haptic guidance with translational inaccuracies (one large inaccuracy, in the order of magnitude of the task, and a second smaller inaccuracy). The quality of natural haptic feedback (i.e., haptic transparency) was varied between high and low to identify the operator's ability to detect and cope with inaccuracies in haptic guidance. The results indicate that haptic guidance is beneficial for task execution when no inaccuracies are present in the guidance. When inaccuracies are present, this may degrade task execution, depending on the magnitude and the direction of the inaccuracy. The effect of inaccuracies on overall task performance is dominated by effects found for the Constrained Translational Movement, due to its potential for jamming. No evidence was found that a higher quality of haptic transparency helps operators to detect and cope with inaccuracies in the haptic guidance.

Design and Implementation of Probe Driver Teleoperative Force Feedback System

The basic need of neurosurgery is to insert the probe into the key hole linearly for performing functional neurosurgery, trigeminal neuralgia surgery, biopsies, deep brain stimulation, and stereo-EEG. Recently, tele-robotic systems have been introduced to assist surgeon during invasive procedures to obtain desired results. In this paper, a linear probe driving tele-operative system with force feedback is proposed. The proposed system is highly accurate, stable, and safe and provides haptic transparency to the surgeon during its operation. The master slave architecture, control system and software application are designed to inject and eject probe driving trials. The experiments are performed on a piecewise linear Plasticine model. The accuracy, stability, repeatability of the system and haptic force feedback fidelity are discussed in the results. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.5277

Control system design of a 3-DOF upper limbs rehabilitation robot

This paper presents the control system design of a rehabilitation and training robot for the upper limbs. Based on a hierarchical structure, this control system allows the execution of sequence of switching control laws (position, force, impedance and force/impedance) corresponding to the required training configuration. A model-based nonlinear controller is used to impose the desired environment to the patient's arm. The knowledge of robot kinematics and dynamics is thus necessary to ensure haptic transparency and patient safety. The identification process of robot dynamics is emphasised and experimental identification results are given for the designed robot. The paper also presents a particular rehabilitation mode named Active-Assisted. Simulation results of this rehabilitation mode illustrate the potentialities of the overall control scheme, which can also be applied to other rehabilitation robots.