Haptic feedback in teleoperation in Micro-and Nano-Worlds.

International audienceRobotic systems have been developed to handle very small objects, but their use remains complex and necessitates long-duration training. Simulators, such as molecular simulators, can provide access to large amounts of raw data, but only highly trained users can interpret the results of such systems. Haptic feedback in teleoperation, which provides force-feedback to an operator, appears to be a promising solution for interaction with such systems, as it allows intuitiveness and flexibility. However several issues arise while implementing teleoperation schemes at the micro-nanoscale, owing to complex force-fields that must be transmitted to users, and scaling differences between the haptic device and the manipulated objects. Major advances in such technology have been made in recent years. This chapter reviews the main systems in this area and highlights how some fundamental issues in teleoperation for micro- and nano-scale applications have been addressed. The chapter considers three types of teleoperation, including: (1) direct (manipulation of real objects); (2) virtual (use of simulators); and (3) augmented (combining real robotic systems and simulators). Remaining issues that must be addressed for further advances in teleoperation for micro-nanoworlds are also discussed, including: (1) comprehension of phenomena that dictate very small object (< 500 micrometers) behavior; and (2) design of intuitive 3-D manipulation systems. Design guidelines to realize an intuitive haptic feedback teleoperation system at the micro-nanoscale level are proposed

3D particle-based cell modelling for haptic microrobotic cell injection

Introducing haptic interface to conduct microrobotic intracellular injection has many beneficial implications. In particular, the haptic device provides force feedback to the bio-operator\u27s hand. This paper introduces a 3D particle-based model to simulate the deformation of the cell membrane and corresponding cellular forces during microrobotic cell injection. The model is based on the kinematic and dynamic of spring &ndash; damper multi particle joints considering visco-elastic fluidic properties. It simulates the indentation force feedback as well as cell visual deformation during the microinjection. The model is verified using experimental data of zebrafish embryo microinjection. The results demonstrate that the developed cell model is capable of estimating zebrafish embryo deformation and force feedback accurately

Virtual haptic cell model for operator training

Microrobotic cell injection is an area of growing research interest. Typically, operators rely on visual feedback to perceive the microscale environment and are subject to lengthy training times and low success rates. Haptic interaction offers the ability to utilise the operator&rsquo;s haptic modality and to enhance operator performance. Our earlier work presented a haptically enabled system for assisting the operator with certain aspects of the cell injection task. The system aimed to enhance the operator&rsquo;s controllability of the micropipette through a logical mapping between the haptic device and microrobot, as well as introducing virtual fixtures for haptic guidance. The system was also designed in such a way that given the availability of appropriate force sensors, haptic display of the cell penetration force is straightforward. This work presents our progress towards a virtual replication of the system, aimed at facilitating offline operator training. It is suggested that operators can use the virtual system to train offline and later transfer their skills to the physical system. In order to achieve the necessary representation of the cell within the virtual system, methods based on a particle-based cell model are utilised. In addition to providing the necessary visual representation, the cell model provides the ability to estimate cell penetration forces and haptically display them to the operator. Two different approaches to achieving the virtual system are discussed

Haptic microrobotic intracellular injection assistance using virtual fixtures

In manual cell injection the operator relies completely on visual information for task feedback and is subject to extended training times as well as poor success rates and repeatability. From this perspective, enhancing human-in-the-loop intracellular injection through haptic interaction offers significant benefits. This paper outlines two haptic virtual fixtures aiming to assist the human operator while performing cell injection. The first haptic virtual fixture is a parabolic force field designed to assist the operator in guiding the micropipette\u27s tip to a desired penetration point on the cell\u27s surface. The second is a planar virtual fixture which attempts to assist the operator from moving the micropipette\u27s tip beyond the deposition target location inside the cell. Preliminary results demonstrate the operation of the haptically assisted microrobotic cell injection system

Haptic guidance for microrobotic intracellular injection

The ability for a bio-operator to utilise a haptic device to manipulate a microrobot for intracellular injection offers immense benefits. One significant benefit is for the bio-operator to receive haptic guidance while performing the injection process. In order to address this, this paper investigates the use of haptic virtual fixtures for cell injection and proposes a novel force field virtual fixture. The guidance force felt by the bio-operator is determined by force field analysis within the virtual fixture. The proposed force field virtual fixture assists the bio-operator when performing intracellular injection by limiting the micropipette tip\u27s motion to a conical volume as well as recommending the desired path for optimal injection. A virtual fixture plane is also introduced to prevent the bio-operator from moving the micropipette tip beyond the deposition target inside the cell. Simulation results demonstrate the operation of the guidance system.<br /

Micro-robotic Cell Injection Training in a CAVE

This paper focuses on the design of an evaluation made to a large-scale virtual reality micro-robotic cell injection training system. The aim of the evaluation is to empirically investigate the usability and effectiveness of three distinct display configurations and the input controller employed in the system. The data was gathered through a set of experiments with human participants. Participants’ performance against metrics such as success rate and magnitude of error was considered in the evaluation. For the experiments, participants were randomly divided into six equal sized groups where each group was provided with a specific combination of display configuration and haptic guidance mode. The participants performed ten injections and the time and position of the virtual micropipette tip were recorded. Data was analysed using descriptive statistics and performance comparison between groups was conducted. Additionally three groups also underwent two subsequent sessions, training and post-training, as a basis to evaluate the effectiveness of the training with haptic guidance by comparing participants’ performance before and after the training session. The implementation of the designed evaluation has contributed to the conclusions drawn which suggest the proposed large-scale virtual reality system as a feasible training tool for micro-robotic cell injection procedure, and recommendations for future work are proposed

Scalability study for robotic hand platform

The goal of this thesis project was to determine the lower limit of scale for the RIT robotic grasping hand. This was accomplished using a combination of computer simulation and experimental studies. A force analysis was conducted to determine the size of air muscles required to achieve appropriate contact forces at a smaller scale. Input variables, such as the actuation force and tendon return force, were determined experimentally. A dynamic computer model of the hand system was then created using Recurdyn. This was used to predict the contact (grasping) force of the fingers at full-scale, half-scale, and quarter-scale. Correlation between the computer model and physical testing was achieved for both a life-size and half-scale finger assembly. To further demonstrate the scalability of the hand design, both half and quarter-scale robotic hand rapid prototype assemblies were built using 3D printing techniques. This thesis work identified the point where further miniaturization would require a change in the manufacturing process to micro-fabrication. Several techniques were compared as potential methods for making a production intent quarter-scale robotic hand. Investment casting, Swiss machining, and Selective Laser Sintering were the manufacturing techniques considered. A quarter-scale robotic hand tested the limits of each technology. Below this scale, micro-machining would be required. The break point for the current actuation method, air muscles, was also explored. Below the quarter-scale, an alternative actuation method would also be required. Electroactive Polymers were discussed as an option for the micro-scale. In summary, a dynamic model of the RIT robotic grasping hand was created and validated as scalable at full and half-scales. The model was then used to predict finger contact forces at the quarter-scale. The quarter-scale was identified as the break point in terms of the current RIT robotic grasping hand based on both manufacturing and actuation. A novel, prototype quarter-scale robotic hand assembly was successfully built by an additive manufacturing process, a high resolution 3D printer. However, further miniaturization would require alternate manufacturing techniques and actuation mechanisms

Haptic technology for micro-robotic cell injection training systems — a review

Currently, the micro-robotic cell injection procedure is performed manually by expert human bio-operators. In order to be proficient at the task, lengthy and expensive dedicated training is required. As such, effective specialized training systems for this procedure can prove highly beneficial. This paper presents a comprehensive review of haptic technology relevant to cell injection training and discusses the feasibility of developing such training systems, providing researchers with an inclusive resource enabling the application of the presented approaches, or extension and advancement of the work. A brief explanation of cell injection and the challenges associated with the procedure are first presented. Important skills, such as accuracy, trajectory, speed and applied force, which need to be mastered by the bio-operator in order to achieve successful injection, are then discussed. Then an overview of various types of haptic feedback, devices and approaches is presented. This is followed by discussion on the approaches to cell modeling. Discussion of the application of haptics to skills training across various fields and haptically-enabled virtual training systems evaluation are then presented. Finally, given the findings of the review, this paper concludes that a haptically-enabled virtual cell injection training system is feasible and recommendations are made to developers of such systems

Virtual Reality simulator for dental anesthesia training in the inferior alveolar nerve block

Objectives This study shows the development and validation of a dental anesthesia-training simulator, specifically for the inferior alveolar nerve block (IANB). The system developed provides the tactile sensation of inserting a real needle in a human patient, using Virtual Reality (VR) techniques and a haptic device that can provide a perceived force feedback in the needle insertion task during the anesthesia procedure. Material and Methods To simulate a realistic anesthesia procedure, a Carpule syringe was coupled to a haptic device. The Volere method was used to elicit requirements from users in the Dentistry area; Repeated Measures Two-Way ANOVA (Analysis of Variance), Tukey post-hoc test and averages for the results’ analysis. A questionnaire-based subjective evaluation method was applied to collect information about the simulator, and 26 people participated in the experiments (12 beginners, 12 at intermediate level, and 2 experts). The questionnaire included profile, preferences (number of viewpoints, texture of the objects, and haptic device handler), as well as visual (appearance, scale, and position of objects) and haptic aspects (motion space, tactile sensation, and motion reproduction). Results The visual aspect was considered appropriate and the haptic feedback must be improved, which the users can do by calibrating the virtual tissues’ resistance. The evaluation of visual aspects was influenced by the participants’ experience, according to ANOVA test (F=15.6, p=0.0002, with