The ability to rapidly acquire novel visuomotor skills is essential for daily functioning tasks such as motor rehabilitation, surgical operation, and mechanical assembly. Previous research suggested that experiencing flow can enhance learning outcomes. Although dynamic difficulty adjustment (DDA) has been commonly used to induce flow and maximize engagement, most existing methods rely on model-free, stepwise adaptations that lack quantitative, model-based support. In this study, we proposed a personalized, model-driven DDA approach to facilitate visuomotor skill acquisition by enhancing flow during the learning process. We implemented an adaptive fine fingertip force control task with DDA based on optimal control principles to train the visuomotor skills. This DDA updated task difficultly using real-time multiple performance metrics, with parameters derived from an individually fitted model that captures each user's motor behavior during the task. A user study, involving two groups, compared the effects of a model-driven adaptive task with a model-free control task. Results from the flow state scale and physiological recordings demonstrated that the model-driven task elicited significantly higher levels of flow than the model-free task. Moreover, participants in the model-driven group showed a notably higher learning rate in visuomotor skills (19%) compared to the model-free group (8%). These findings underscore the potential of integrating personalized modeling and optimal control theory to optimize user experience and accelerate learning outcomes in DDA frameworks when building adaptive human–machine interaction systems.

Touchscreen devices often suffer from high typing error rates in the absence of physical keys. Shape-changing displays, which recreate physical keys on the screen, offer a promising solution. While the travel of physical keys plays an important role in the typing experience, it has received limited attention in previous work. To investigate the impact of on-screen physical keys with varying key travel on typing performance and user preferences, we developed a fully transparent shape-changing display that delivers adjustable key travel on touchscreens. The engineered portable microfluidic pressure-control system regulates the driving pressure, thereby adjusting the key travel to provide personalized passive tactile feedback. Using this platform, we conducted a user study in which participants typed with a two-thumb posture under four different key travel conditions, including the zero-travel condition. The results demonstrate that shape-changing keys significantly reduce typing error rates compared with flat keys, while revealing significant inter-individual variability in both performance and preference. These findings highlight the role of adjustable key travel in meeting diverse user needs and enabling adaptive touchscreen interaction.

Flow, an optimal mental state merging action and awareness, significantly impacts our emotion, performance, and well-being. However, capturing its swift transitions on a fine timescale is challenging due to the sparsity of the existing flow detecting tools. Here we present a fine fingertip force control (F3C) task to induce flow, wherein the task challenge is set at a compatible level with personal skill, and to quantitatively track the flow state variations from synchronous motor control performance. We select eight performance metrics from fingertip force sequence and reveal their significant differences under distinct self-reported flow states. Further, we built a machine learning-based decoder that aims to predict the continuous flow intensity during the user experiment through the performance metrics, taking the self-reported flow as the label. Cross-validation shows that the predicted flow intensity reaches significant correlation with the self-reported flow intensity (r= 0.81). Based on the decoding results, we can capture the flow fluctuations during the intervals between sparse self-reporting probes. This study showcases the feasibility of tracking intrinsic flow variations with high temporal resolution using task performance measures and may serve as foundation for future work aiming to take advantage of flow's dynamics to enhance performance and positive emotions.

Due to the lack of physical touch, social distancing caused by COVID-19 makes it difficult to convey social intentions through handshakes. To mitigate this situation, one promising solution is to simulate distinguishable handshake patterns through haptic feedback devices during distant social communication. This paper reports a distant handshake scheme with multi-modal soft haptic gloves. To address the challenge of duplicating rich haptic stimuli of real handshakes in a compact glove, we extracted four haptic features including grip location, grip strength, skin temperature, and shaking frequency from abundant components of the haptic perception system to mimic handshake behaviors. To guide the interference-free spatial layout of multiple actuators in a limited hand-sized space, we measured the handshake contact area and grip strength of different handshake patterns, which together with the thermosensitivity of the human hand determine the grip location, grip strength, and salient thermal stimulating location. We developed a multi-modal soft haptic glove by rendering four features through pneumatic pressure, thermal, and vibrotactile stimuli, respectively. A user study was conducted to validate the performance of our glove, which set two states for each of the four features, showing over 90% accuracy in distinguishing 16 handshake patterns. Furthermore, a user study on the identification of social intentions yields the finding that distant handshakes with our haptic gloves can convey positive, neutral, and negative social intentions. These results inform the potential of distant handshakes with haptic gloves to convey social intentions in remote interactions including business, politics, and daily life in severe and post-pandemic situations, as well as in future metaverse-based society.

Touch interaction is one of the fundamental interaction paradigms in XR, as users have become very familiar with touch interactions on physical touchscreens. However, users typically need to perform extensive arm movements for engaging with XR user interfaces much larger than mobile device touchscreens. We propose the SummonBrush technique to facilitate easy access to hidden windows while interacting with large XR user interfaces, requiring minimal arm movements. The SummonBrush technique adds a virtual brush to the index fingertip of a user's hand. Upon making contact with a virtual user interface, the brush bends and diverges and ink starts to diffuse in it. The more the brush bends and diverges, the more the ink diffuses. The user can summon hidden windows or background applications in situ, which is achieved by firstly pressing the brush against the user interface to make ink fully fill the brush and then perform swipe gestures. Also, the user can press the brush against the thumbtails of background applications in situ to quickly cycle them through. Ecological studies showed that SummonBrush significantly reduced the arm movement time by 39% and 34% in summoning hidden windows and activating/closing background applications, respectively, leading to a significant decrease in reported physical demand.

High-fidelity tactile rendering offers significant potential for improving the richness and immersion of touchscreen interactions. This study focuses on a quantitative description of tactile rendering fidelity using a custom-designed hybrid electrovibration and mechanical vibration (HEM) device. An electrovibration and mechanical vibration (EMV) algorithm that renders 3D gratings with different physical heights was proposed and shown to achieve 81% accuracy in shape recognition. Models of tactile rendering fidelity were established based on the evaluation of the height discrimination threshold, and the psychophysical-physical relationships between the discrimination and reference heights were well described by a modification of Weber’s law, with correlation coefficients higher than 0.9. The physiological-physical relationship between the pulse firing rate and the physical stimulation voltage was modeled using the Izhikevich spiking model with a logarithmic relationship.

When we enter Virtual Reality (VR) in the first person, the avatar replaces our real body. Within a certain range of mismatches, we tend to identify with our avatar and perceive it as our own body. Previous research has shown that we can even believe that a deformed forearm is our own through haptic and visual feedback. However, the haptic devices used in earlier research were only explored using skin-stretching and weight-shifting. Vibrotactile feedback is the most common technique used to create a haptic VR experience in academia and industry because of its light weight and ease of application. Taking these advantages, we introduce VibroArm, a lightweight wearable haptic system with the vibrotactile funneling illusion that enhances the virtual forearm’s ownership in the forearm deformation illusion. In a perceptual study, we determined that users can make correct direction judgments about vibration on the forearm in different directions. The result shows that all vibration patterns can be sufficiently recognized, with an average recognition rate of $87.17 \%$. Based on our results, we designed 18 vibration patterns and compared their impact on the forearm deformation illusion. Finally, our study shows that using VibroArm in VR applications can significantly improve user realism and enjoyment compared to relying on visual feedback alone.

Compared to wearable devices, handheld haptic devices are promising for large scale virtual reality applications because of their portability and capability of supporting large workspace haptic interaction. However, it remains a challenge to render multimodal haptic stimuli in handheld devices due to space confinement. In this paper, we present a modular approach to build a Multimodal Handheld Haptic Controller called “Haptic Handshank” that includes a thumb feedback component, a palm feedback component, and a motion tracking component. In the thumb feedback component, a compact pneumatically-driven silicone airbag is utilized to simulate softness, and a flexible membrane based on the electro-vibration principle which covers the top portion of the airbag for rendering virtual textures. In the palm feedback component, vibrational motors and Peltier devices are embedded into the device's body for rendering vibrotactile flow and distributing thermal stimuli. In the motion tracking component, an HTC-Vive tracker is mounted on the bottom of the controller's handle to enable 6-DOF palm motion tracking. The performance of the handheld device is evaluated through quantitative experimental studies, which validate the ability of the device to simulate multimodal haptic sensations in accordance with diverse hand manipulation gestures such as enclosure, static contact, rubbing, squeezing and shaking of a cup of cold drink in 3D virtual space.

Immersion, interaction, and imagination are three features of virtual reality (VR). Existing VR systems possess fairly realistic visual and auditory feedbacks, and however, are poor with haptic feedback, by means of which human can perceive the physical world via abundant haptic properties. Haptic display is an interface aiming to enable bilateral signal communications between human and computer, and thus to greatly enhance the immersion and interaction of VR systems. This paper surveys the paradigm shift of haptic display occurred in the past 30 years, which is classified into three stages, including desktop haptics, surface haptics, and wearable haptics. The driving forces, key technologies and typical applications in each stage are critically reviewed. Toward the future high-fidelity VR interaction, research challenges are highlighted concerning handheld haptic device, multimodal haptic device, and high fidelity haptic rendering. In the end, the importance of understanding human haptic perception for designing effective haptic devices is addressed.

Based on the integrated design concept of using the robot's mechanical arm for both locomotion and manipulation, we proposed a compact and transformable robot, i.e. the WALS-Robot, which utilizes combination and switch among four components: wheels, arms, legs and suckers. The WALS-Robot could transform among five locomotion modes to fulfill locomotion requirements in indoor unstructured environments, and have dexterous manipulation, and low power consumption. To reduce the redundancy of mechanical structure and the moving payload for the robot, the mobile platform and the mechanical arm could work as a unity, i.e. the mechanical arm can switch into a leg of the robot to reduce payload during moving modes. Experimental results validated key performance of the robot, including locomotion accuracy and efficiency, compact volume and low power consumption. The integrated design concept illustrated the adaptability in diverse unstructured indoor environments, enlarging the manipulation workspace, and enhancing the energy efficiency.

Controlling absolute magnitudes of fingertip force is an important skill in many haptic interactions such as surgical operations and mechanical assemblies. A fundamental question in the force control is how quickly human can output a target force with expected accuracy. In this paper, human's capability to control absolute magnitudes of fingertip force under audio or visual feedback was observed through experiments. Twelve participants applied a target force by pressing a force sensor with their fingers and maintained the force within a specified tolerance for a specific period of time (500ms). The magnitudes of target force and tolerance were manipulated systematically to yield varied levels of task difficulty. The experimental data showed that the applied fingertip force obeyed Fitts' law under both visual and auditory feedback modes when the index of difficulty (ID) was smaller than a threshold. The results may be used as guidelines for the applications that rely on accurate and quick changing force control over a target region such as multiple tapping tasks.

Compared with single-modal sensorimotor task, cross-modal sensorimotor tasks such as Tai Chi are more complex because they require simultaneous control of joint motion and respiration. In this paper, we compared the performance of single and multi-sensory cues in single-modal and cross-modal tasks. The experimental results showed that for single-modal task of two joint motions, the performance of using both audio and vibrotactile cues was slightly worse than that of using single-sensory cues where both joints were guided by vibrotactile cues, which implied that the single-sensory cue was more suitable for the single-modal motor tasks while the multi-sensory cues might produce distraction to participants. For simultaneous control of joint motion and respiration, the multiple sensory cues produced better performance than the single sensory cues. The results implied that multi-sensory cues were more effective than single sensory cues in reducing mental workload when learning complex cross-modal motor tasks.

The capability of applying a weak force with expected accuracy is an important motor skill in surgical operations. Acquiring such a skill is challenging for novices. In this paper, we studied how the accuracy of the force control could be enhanced through repetitive training. Twelve participants were divided into two groups. They were trained to apply a target force of 0.25N with ±20% accuracy under concurrent visual feedback (Group A) and delayed visual feedback (Group B). After each training session, a test was conducted to measure the force applied by participants without any feedback. The results show that Group B achieved the expected accuracy faster than Group A. The experimental data suggests that the delayed visual feedback appears to be more effective on consolidating motor memory in the force control task. Our finding opens a new opportunity to further explore the relationship between feedback and cognitive process (i.e. attention and motor memory) of motor skill learning.

Tooth extraction is a typical process in clinical dental operations. Interactive haptic simulation of tooth extraction may provide a useful tool for dental students to learn the correct force pattern and tool posture to accomplish a safe tooth extraction. In this paper, we extended our previous configuration-based optimization approach to simulate the six Degree-of-Freedom (DoF) haptic interaction process of tooth extraction. A multi-phase model was proposed to simulate progressive changes of the connection strength between the target tooth and its surrounding gingiva. An energy accumulation model was proposed to compute the small-scale rotation and translation of the target tooth under active forces from a dental forceps. The proposed approach could support training of coordinated force and motion control skill required for tooth extraction. Experimental results validated the stability and efficiency of the proposed approach to simulate various force-displacement profiles for extracting diversified target teeth.

Simultaneous motion control of multiple joints has many potential applications such as Tai Chi, Yoga etc. The capability of vibrotactile cues to assist this kind of motor task has not been well explored. In this paper, we studied the effect of vibrotactile cues for guiding procedural motion of two joints on human's upper limbs. By mounting eight vibrotactile motors on two arms, we performed two experiments to measure human's perception and motor performance in response to the vibrotactile commands. In the first experiment, we measured perceptual performance of correctly identifying the location of two active vibrotactile cues. The difference between sustained, pulsed and hybrid vibration conditions was compared. To explore the possible reasons leading to the wrong perception results, the correct rate was ranked among different combinations of cues. In the second experiment, the correct rate of procedural motion control of two joints was measured, while vibrotactile cues were used as guidance signals to produce the motion command. The results showed that average correct rate of two cues localization on upper limbs was as high as 98%, while the average correct rate of procedural motion control of two joints was only 86%. Further analysis revealed that low correct rate of procedural motion control was caused by the unnatural motion pattern, i.e. two joints on a same arm and rotate in opposite directions.

In this paper, we proposed a 3D path planning method for a miniature robotic system, which can manipulate a beam of ultra-short pulse laser to cut a decayed tooth to formulate an expected 3D shape. Using high resolution STereo Lithography (STL) models of the original decayed tooth and the target preparing shape as the input, our method consists of a fast slicing algorithm and an optimized path generating algorithm, which realized a high efficient layer-by-layer cutting for laser ablation. Theoretical analysis on the geometric distortion and surface roughness was carried out to model the influence of the path planning algorithms on the accuracy of the prepared tooth. Experimental results on a real tooth indicate that the path planning method can maintain the accuracy for the laser ablation process.

This paper presents a modified master-slave motion mapping method for space teleoperation using haptic device with limited workspace. The method combines rate control and a variable scaled position mapping to realize accurate and efficient teleoperation. Haptic feedback in these two mapping modes is designed with emphasis on ergonomics to improve immersion of teleoperation. A dead zone is defined in master side to guarantee system stability when mode switches. We illustrate our method on teleoperation path tracking and target positioning tasks and compare the results with two widely used methods: rate control and scaled position mapping. The comparison experimental results demonstrate that the proposed hybrid motion mapping method is the most efficient method for path tracking and the most accurate one for target positioning.

The handle-avatar mapping from the handle of a desktop haptic device (i.e., the handle) to the virtual tool (i.e., the avatar) is subject to several uncertainties, including uncertain held positions of the human hand, un-modeled hand position on the virtual tool, and difference between the shape of the virtual tool and that of the physical handle. The influence of these uncertainties on the force/torque fidelity of 6-DOF haptic rendering is analyzed in this paper. A model of force/torque error induced by these uncertainties is introduced to measure the influences under different contact scenarios. A method based on adding a handle-hand avatar to the virtual tool is proposed to reduce the uncertainties and thus to improve simulation fidelity. Psychophysical experiments were carried out. Experiment results show that the subjective feeling of the human operator is consistent with the theoretical analysis results. Most subjects can feel the increase on torque fidelity after using the proposed method.

Auditory or visual stimulation has been widely used for brainwave entrainment, i.e. to modulate brain electroencephalograms (EEG) signals into a specific target frequency band. In this work, we study whether similar phenomena exists with haptic stimulation. By using a Phantom desktop to provide a sinusoidal force stimulation to a human subject's hand, and using a Nexus EEG device for real-time brain signal monitoring, we test how the Sensory Motor Rhythm (SMR) signal and the Alpha signal of the subject responds to the haptic stimulation. Our experiments show that the energy level of SMR signal tends to increase considerably (on average 10~30% of 8 human subjects) after 10-15 minutes of haptic stimulation with a 15Hz stimulation signal, and the energy level of Alpha signal tends to decrease considerably (on average 10~30% of 8 human subjects) after 10-15 minutes of haptic stimulation with a 10Hz stimulation signal. These results may have potential application in training human concentration and/or relaxation skills.

In-vivo measurement of force/torque signals between a surgical tool and human vessels during vascular surgery operations could provide a ground-truth data-set for constructing and evaluating haptics-enabled surgical simulation systems. In this paper, we introduce a novel wearable device for measuring such signals. This new design provides much higher measurement accuracy than a previous prototype. Experimental results by using standard weights provide that the relative force and torque error is about 5%. With time-varying load, the new device is compared with an ATI Nano17 force/torque sensor; average relative errors between the force signals is about 16.85%, and average relative errors between the torque signals is about 28.74%. Preliminary manipulation experiments of inserting a catheter into a vascular phantom model illustrated that the device can detect the collision between the catheter and the vascular walls. Subtle force/torque changes caused by changes of movement direction can be detected. Force/torque changes at some critical point (such as the interaction point of vessels) can also be detected.

As a preliminary step to achieve a long-term goal of developing an automatic dental preparation system for clinical operations, we design and build a miniature robotic system which can manipulate a laser beam to move in three dimensional spaces to remove hard tissue from a target tooth. The dental preparation requires the robotic system to own high accuracy, high ablation speed and small size. A 2D galvanometer scanners module is integrated to meet the requirement of a high moving speed of the laser focus. A closed-loop system based on a miniature-sized voice-coil motor and a grating ruler are developed to realize the accurate control of the focus. The overall size of the developed prototype is 108mm×56mm×43mm, which is small enough to be used in close proximity to a patient's mouth. The prototype has been tested by using two different kinds of laser generators, i.e., a nanosecond laser and a picosecond laser. The experiment results show that the robotic system can provide high moving speed of 1000mm/s with good shape accuracy. From the results, we found that nanosecond laser beam can be controlled to ablate zirconia and aluminum, but not suitable to ablate tooth because of tissue carbonization. By selecting suitable parameters of the picosecond laser generator, a target tooth could be ablated to produce a cylinder shape without carbonization. Limitations of the prototype are identified according to the experiment results.

It is a challenging problem to achieve fast and realistic six degree-of-freedom (DOF) haptic simulation of scenarios involving large number of multi-region contacts. In this paper, we propose an optimization-based constrained method enhanced by parallel quadratic programming to solve the rendering problem. Hierarchical sphere-tree models are used to represent the moving haptic tool and its surrounding static objects. Given a moving graphic tool as the avatar of the haptic tool in the virtual environment, we compute its quasi-static motion by solving a configuration-based optimization. Instead of using traditional active-set method, we transform the original optimization problem into its dual problem and solve the optimum about the graphic tool using a parallel quadratic programming method. Our algorithm has been implemented with a 6-DoF Phantom Premium 3.0. We validate the proposed algorithm in several benchmarks involving complex, large-region contacts. The results demonstrate that the proposed method can achieve a two to three times speed improvement than the active-set method. A further speed-up for haptic rendering may be achieved by the parallel implementation on parallel processor such as graphic processing units.

Six-degree-of-freedom (6-DOF) haptic rendering is challenging when multi-region contacts occur between the graphic avatar of a haptic tool operated by a human user, which we call the graphic tool, and deformable objects. In this paper, we introduce a novel approach for deformation modeling based on a spring-sphere tree representation of deformable objects and a configuration-based constrained optimization method for determining the 6-dimensional configuration of the graphic tool and the contact force/torque response to the tool. This method conducts collision detection, deformation computation, and tool configuration optimization very efficiently based on the spring-sphere tree model, avoids inter-penetration, and maintains stability of haptic display without using virtual coupling. Experiments on typical dental operations are carried out to validate the efficiency and stability of the proposed method. The update rate of the haptic simulation loop is maintained at ~1kHz.

Geometric modeling and haptic simulation of pathological changes is an important topic for high-fidelity surgical simulators. In this paper, we introduce a constraint-based six degree-of-freedom (DOF) haptic simulation method incorporating multi-contact friction. We use this method to simulate periodontal operations on typical pathological tissues, including periodontal pocket and two kinds of calculi. A continuous collision detection method based on sphere-trees is proposed to avoid the pop-through phenomenon during tool manipulation against thin objects (such as small sized calculus adhered to the surface of the target tooth). For particle shaped calculus, a friction model is adapted to simulate decreasing frictions during the removal of the calculus. Experiments using a Phantom Premium 3.0 6DOF were carried out to validate the performance of our method. Stable haptic rendering and about 1 kHz update rate was maintained for all the operations, including depth measurement of the periodontal pocket and removal of the invisible block-shaped and particle-shaped calculi.

Subtle force feelings caused by contacts at sharp geometric features are necessary to achieve high-fidelity haptic rendering. It is a challenging problem to achieve six degree-of-freedom (6-DOF) haptic simulation with sharp features for multi-region contacts scenario. We propose a configuration-based optimization method using a hybrid sphere-tree model to compute constraint-based collision response. Based on the variance of dihedral angle between adjacent triangles, an original triangle mesh of the simulated object is segmented into a hybrid sphere-tree model, i.e. a hierarchical sphere-tree for global shape and several linear-lists of spheres for local areas with sharp features. In each local area with sharp features, we first identify those spheres which radius is larger than a pre-defined perceptual threshold. Then these spheres are divided into a linear list of smaller spheres by a splitting method. The experiment results on a sphere-cube interaction and a spline-shaped peg-hole interaction validate that the proposed method can simulate a subtle force direction change when sliding contact occurs across the sharp edges. Non-penetration between the two objects can be maintained for multi-region contacts scenario. The haptic rendering rate is over 1kHz and the interaction is stable.

Virtual coupling is commonly used to maintain stability of penalty-based haptic rendering. However, due to dozens of design parameters involved in the dynamics and force model, to increase transparency while maintaining stability using virtual coupling remains a challenge for 6-Degree-of-Freedom (DOF) haptic rendering. Using an equivalent-angle analysis, we transform 3-DOF rotation into 1-DOF rotation, thereby transforming the 6-DOF dynamics into six 1-DOF dynamics. For each 1-DOF dynamics, a damped vibration model is proposed to analyze the computation of the `graphic tool'. The equilibrium position/angle is defined to analyze the convergence of numerical integration. With this approach, we can improve the transparency of 6-DOF haptic rendering in both free space and constraint space by experimentally determining only two parameters: the integration time step and the number of integrations in each simulation loop. Using this method, we can improve the coupling stiffness to fully exploit the display capability of the haptic device and maintain the stability of the haptic rendering.

Six-degree-of-freedom (6-DOF) haptic rendering for fine manipulation in narrow space is a challenging topic because of frequent constraint changes caused by small tool movement and the requirement to preserve the feel of fine-features of objects. In this paper, we introduce a configuration-based constrained optimization method for solving this rendering problem. The six-dimensional configuration (position and orientation) of the graphic tool is defined as the solution variable of the optimization problem Contact constraints are obtained based on identifying principal contacts between the graphic avatar of the haptic tool, called the graphic tool, and the virtual task environment. In order to maintain stability during contact switch, a hybrid method combining collision detection, local search and parallel optimization is introduced. Based on parallel optimization and selection of local solution, we can maintain the local solution of the optimization model. Our method has been validated in experiments of moving a convex tool to probe a narrow cavity with or without bulges. Force rendering is stable even when the free space is very small and involves fine features of objects. Non-penetration between the tool and the object forming the cavity are maintained under frequent contact switches. Update rate of the simulation loop including the optimization and constraint identification is maintained at about 1kHz.

This paper presents a novel constraint-based six degree-of-freedom (6-DoF) haptic rendering algorithm for simulating both contact forces and torques between interacting rigid bodies. We represent an object using a hierarchy of spheres, i.e., a sphere-tree. Such a representation allows fast detection of multiple contacts/collisions among objects and facilitates contact constraint formulation. Given a moving graphic tool as the avatar of the haptic tool in the virtual environment, we constrain its position and orientation, i.e., its six dimensional configuration, by solving a constrained optimization problem. The constraints in the 6-D configuration space (C-space) of the graphic tool is obtained and updated through on-line mapping of the non-penetration constraint between the spheres of the graphic tool and those of the other objects in the three dimensional physical space, based on the result of collision detection. The problem is further modeled as a quadratic programming problem and solved by classic active-set methods. Our algorithm has been implemented and interfaced with a 6-DoF Phantom Premium 3.0. We demonstrate its performance in dental surgery simulations involving complex, multi-contact virtual environments. Our method enables stable operations and realistic feel of haptic sensation.

Abstract Piecewise linear polygonal model has onlyG0continuity, thus users can easily feel the edges when using haptic device to touch a solid represented by coarse polygonal meshes. To produce an appealing haptic sensation for smooth solids, a large number of polygons are needed in conventional approaches. This, however, slows down computation and consumes much more memory. In this paper, we present a method to generate smooth feedback force in haptic interaction with coarse polygonal meshes. Our method calculates the interaction force based on Gregory patches, which are locally constructed fromn‐sided polygons and ensureG1continuity across boundaries of patches. During the real time haptic interaction, the contact point is continuously tracked on the locally constructed Gregory patches and thus generates smooth haptic forces to be rendered. Our method is validated on various models with comparison to conventional force rendering techniques. Copyright © 2010 John Wiley & Sons, Ltd.

This paper presents a new six DOF haptic device for dental surgery training system, which can provide 6 dimensional virtual force and torque. The proposed haptic device is based on a modified 6-RSS parallel mechanism. Small inertia of the device is obtained by locating all the actuators on the fixed platform. The inverse and forward kinematics of the device is solved by a new numerical method. Singular configurations are identified and prevented from being within the required task workspace. The required force and torque is achieved within the task workspace. The performance of the device has been proved satisfying the design requirements.

Training of motor skill through machine-mediated method is a promising way to improve complex dexterous manipulation skill. New method of fusion between human motor skill and machine capability is studied to transfer skill from expert to novice. Haptic-enabled Chinese handwriting training system is established as a benchmark platform for studying learning and transfer of motor skill. Perceptible element of haptic skill is proposed to model human motor skill. Four rules of machine-mediated training system are identified according to human's skill learning characteristics. Architecture of a hierarchical hybrid control training system is proposed based on the learning rules. Phantom desktop is used as the haptic interface and haptic-visual feedback is developed for three training modes, which includes facsimile mode, transcribe mode and reciting mode. Human subject experiments validate the proposed training rules. Fusion of human skill and machine capability by haptic-enable multiple signal feedback system is proved effective to train novice to get familiar with Chinese character handwriting skill

This paper presents a cutting force model for dental training system with haptic display capability. The force model is proposed by theoretic analysis of the cutting force between dental tools and tooth. A damping matrix is developed for obtaining a unified formulation for all components of cutting forces. All factors that affect the cutting force are considered in the model by including a number of parameters. These parameters are identified by tooth-cut experiments, which measure the cutting force with a six-dimensional force sensor. A prototype system of haptic simulation is developed to test the model. Dentists performing virtual operation on the system have confirmed the realistic sense of cutting force.