Partner-sourced haptic feedback rather than environmental inputs drives coordination improvement in human dyadic collaboration

How does haptic feedback during a human-virtual human interaction affect emotional arousal in virtual reality? In this between-subjects study, we compare haptic feedback and no haptic feedback conditions in which a virtual human "bumps" into the participant in order to determine the influence of haptic feedback on emotional arousal, sense of presence, and embodiment in virtual reality, as well as compare self-report measures of emotional arousal to those objectively collected via event-related galvanic skin response (GSR) recordings. We plan to extend the current preliminary study by adding three more conditions as described in the future work section. Participants are students age 18-32 with at least moderate experience in virtual reality. Preliminary results indicate significant differences in presence and embodiment between haptic feedback and no haptic feedback groups. With our small sample size at the current time, GSR does not show significant differences between haptic and no haptic feedback conditions.

Manual preferences for visually- and haptically-guided grasping

Recently a number of TV manufacturers introduced TV remotes with a touchpad which is used for indirect control of TV UI. Users can navigate the UI by moving a finger across the touch pad. However, due to the latency in visual feedback, there is a disconnection between the finger movement on the touchpad and the visual perception in the TV UI, which often causes overshooting. In this paper, we investigate how haptic feedback affects the user experience of the touchpad-based TV remote. We described two haptic prototypes built on the smartphone and Samsung 2013 TV remote respectively. We conducted two user studies with two prototypes to evaluate how the user preference and the user performance been affected. The results show that there is overwhelming support of haptic feedback in terms of subjective user preference, though we didn't find significant difference in performance between with and without haptic feedback conditions.

The ability to track a moving target with the hand has been extensively studied, but few studies have characterized gaze behavior during this task. Here we investigate gaze behavior when participants learn a new mapping between hand and cursor motion, such that the cursor represented the position of a virtual mass attached to the grasped handle via a virtual spring. Depending on the experimental condition, haptic feedback consistent with mass-spring dynamics could also be provided. For comparison a simple one-to-one hand-cursor mapping was also tested. We hypothesized that gaze would be drawn, at times, to the cursor in the mass-spring conditions, especially in the absence of haptic feedback. As expected hand tracking performance was less accurate under the spring mapping, but gaze behavior was virtually unaffected by the spring mapping, regardless of whether haptic feedback was provided. Specifically, relative gaze position between target and cursor, rate of saccades, and gain of smooth pursuit were similar under both mappings and both haptic feedback conditions. We conclude that even when participants are exposed to a challenging hand-cursor mapping, gaze is primarily concerned about ongoing target motion suggesting that peripheral vision is sufficient to monitor cursor position and to update hand movement control.

Haptic feedback with bidirectional communication can effectively enhance the realism and immersion in human-machine interaction. In this work, we propose the FlexHapComm interface, a flexible wearable haptic communication interface that functions as an electronic-skin system. It enables dynamically programmable shape-morphing haptic feedback patterns and supports real-time bidirectional haptic interaction by cointegrating actuation and sensing units. The interface designs an array of hydraulic amplified self-healing electrostatic (HASEL) actuators, each with a diameter of 8 mm and capable of generating up to 150 mN of haptic feedback force. Meanwhile, sponge-like pressure sensors are integrated to provide relatively good sensitivity and excellent mechanical compliance suitable for skin-mounted operation. A multichannel programmable control system independently drives and regulates the actuation and sensing units, allowing precise and synchronized bidirectional haptic communication. Interpersonal interaction experiments verify the high-accuracy transmission and perception of tactile signals, while applications such as gesture training and sign language learning demonstrate the potential of haptic feedback for real-time corrective guidance. This study provides a new technological paradigm for skin-wearable communication platforms, opening a promising avenue toward natural, efficient, and immersive tactile interaction.

The perceptual deadband (PD) data reduction scheme allows for a significant reduction of network load in real-time haptic communication scenarios. Aiming to ascertain how the optimum PD data reduction parameter k is best determined, an experiment was conducted in which a possible interaction of PD data reduction and visual feedback on haptic feedback quality and task performance was investigated. The results show that when haptic feedback is complemented with visual feedback, haptic data reduction affects haptic feedback quality at a lower data reduction rate than it affects task performance. When visual feedback is missing, however, this effect is reversed. These results imply that the perception of haptic feedback quality is markedly influenced by visual sensory input as well as task requirements; hence, it is recommended to consider feedback quality and task performance in the optimization of PD reduction before such schemes may be applied to industrial telepresence and teleaction systems.

Web-based human-robot collaboration digital twin management and control system

This paper describes an experiment that studies the effect of basic haptic feedback in creating a sense of social interaction within a shared virtual environment (SVE). Although there have been a number of studies investigating the effect of haptic feedback on collaborative task performance, they do not address the effect it has in inducing social presence. The purpose of this experiment is to show that haptic feedback enhances the sense of social presence within a mediated environment. An experiment was carried out using a shared desktop based virtual environment where 20 remotely located couples who did not know one another had to solve a puzzle together. In 10 groups they had shared haptic communication through their hands, and in another group they did not. Hence the haptic feedback was not used for completing the task itself, but rather as a means of social interacting – communicating with the other participant. The results suggest that basic haptic feedback increases the sense of social presence within the shared VE.

The emergence of Industry 5.0 brings a paradigm shift towards collaborative environments where humans and intelligent robots work side-by-side, enabling personalized, flexible, and resilient manufacturing. However, integrating humans and robots introduces new operational and safety risks that require proactive and adaptive control strategies. This study proposes an intelligent multi-criteria decision-making framework for smart risk assessment and the selection of optimal adaptive control strategies in human–robot collaborative manufacturing settings. The proposed framework integrates advanced risk analytics, real-time data processing, and expert knowledge to evaluate alternative control strategies, such as real-time wearable sensor integration, vision-based dynamic safety zones, AI-driven behavior prediction models, haptic feedback, and self-learning adaptive robot algorithms. A cross-disciplinary panel of ten experts structures six main and eighteen sub-criteria spanning safety, adaptability, ergonomics, reliability, performance, and cost, with response time and implementation/maintenance costs modeled as cost types. Safety receives the most significant weight; the most influential sub-criteria are collision avoidance efficiency, return on investment (ROI), and emergency response capability. The framework preserves linguistic semantics from elicitation to aggregation and provides a transparent, uncertainty-aware tool for selecting and phasing adaptive control strategies in Industry 5.0 collaborative cells.

Transfer of skills and teaching tasks to robots face new challenges when the demonstrations are provided remotely via tele-operation. Not only having a remote operator, but also the communication between the tele-operator and the operator affects the quality of demonstrations. Artifacts introduced by lossy haptic data compression and communication delay deteriorate the system transparency; however, the impact of these on the quality of learning has not been studied yet. In this paper, we construct the bridge between the learning quality and the reduced transparency caused by lossy haptic data compression during teleoperation with haptic feedback. The considered haptic data compression scheme is the previously proposed perceptual dead band-based kinesthetic data reduction approach. The learning quality is assessed both with the mean squared error (MSE) metric on the trajectory level and with the rate of success defined on the task requirement. Our experiments show that the learning quality is reduced significantly for a dead band parameter larger than 20% and 30% for a cube following and peg-in-hole tasks, respectively.

The combination of virtual reality (VR) and human-robot collaboration has revolutionized surgical procedures by providing immersive control, heightened accuracy, and improved coordination between the surgeon and the robot. This interaction allows for complex procedures that require increased flexibility and reduced invasiveness. Existing control algorithms are challenged with latency, limited multimodal data fusion, and an inability to adapt to newly updated surgical environments; thus, they are prone to reduced accuracy, suboptimal force control, or unsynchronized human and robot control. This article introduces a novel Adaptive Multimodal Reinforcement Learning (AMRL) framework that effectively incorporates visual, haptic, and auditory feedback for dynamic surgical control in a VR environment. The AMRL technique employs a continuous learning capability that allows the robot to learn from multimodal data and human intent, enabling responses utilizing real-time touch, sight, and sound. This enhanced adaptability facilitates coordination and accuracy of surgical procedures while reducing latency. The method will be applied and tested in Robotic-Assisted Laparoscopic Surgery (RALS), allowing the system to adapt in real-time to tissue changes and complex motion requirements. Experimental results demonstrate that the AMRL framework improves task completion accuracy, motion smoothness, and interaction efficiency compared to traditional multimodal control algorithms, creating a safer, more intuitive, and effective human-robot collaboration system for surgical practice.

The aim of study is to complement and enhance the haptic sensation of human fingers that have different tactile perceptions owing to the age and proficiency. In this paper, we developed a wearable haptic augmentation system to modulate the haptic sensations in real-time using polyvinylidene fluoride (PVDF) skin vibration sensor and vibro-tactile feedback. We observed that the users could get more exhilarating experiences when touching the surrounding objects, and recognition of haptic properties became easier. The experimental result shows that the haptic sensation obtained by our proposed condition is approximately 5% higher than the no haptic feedback condition.

The effectiveness of virtual environments in developing collaborative strategies between industrial robots and humans

The change in production towards smaller batch sizes demands a high degree of flexibility, especially in assembly. In this context, human-robot collaboration (HRC) is becoming increasingly important. The goal is not to displace the human being by the robot, but instead receiving support from it. Nevertheless, employees at all levels have to be prepared for the HRC. Trainings offered from robot manufacturers focus on robot specific operations and are not sufficient for the development of competencies for innovative and creative process planning and optimisation. Therefore, a mixed reality learning environment can be used for the implementation of such training, since real production facilities are only available to a limited extent for training purposes. In the context of the implementation of a mixed reality learning environment, the question arises as to the necessity of haptic feedback. This article presents a concept for integrating HRC in German initial and continuing vocational education and training using mixed reality.

In this paper, our purpose is to study the quaternary continuous classical boundary optimal control vector problem dominated by a quaternary linear parabolic boundary value problem. Under suitable assumptions and with a given quaternary continuous classical boundary control vector, the existence theorem for a unique quaternary state vector solution to the weak form is stated and demonstrated via the method of Galerkin. Furthermore, the continuity of the Lipschitz operator between the state vector solution to the weak form for the dominating equations and the corresponding are proved. The existence of a quaternary continuous classical boundary optimal control vector is stated and demonstrated under suitable Assumptions. The mathematical formulation for the quaternary adjoint boundary value problem associated with each considered boundary value problem is obtained and the Frѐchet derivative for the objective function is derived. Finally, the necessary conditions for the optimality theorem of the problem are stated and demonstrated.