Search

Human--robot co-carrying tasks demonstrate their potential in both industrial and everyday applications by leveraging the strengths of both parties. Effective control of robots in these tasks requires minimizing position and velocity errors to complete the shared tasks while also managing the energy level within the closed-loop systems to prevent potential dangers such as instability and unintended force exertion. However, this collaboration scenario poses numerous challenges due to varied human intentions in adapting to workspace characteristics, leading to human--robot conflicts and safety incidents. In this paper, we develop a robot controller that enables the robot partner to re-plan its path leveraging conflict information, follow co-carrying motions accurately, ensure passivity, and regular the energy of the closed-loop system. A cooperation control framework for human--robot co-carrying tasks is constructed by utilizing admittance control and time-varying Passive Velocity Field Control with a fractional exponent energy compensation control term. By measuring the interaction force, the desired trajectory of co-carrying tasks for the robot partner is first generated using admittance control. Thereafter, the new Passive Velocity Field Control with the energy compensation feature is designed to track the desired time-varying trajectory and guarantee passivity. Furthermore, the proposed approach ensures that the system's kinetic energy converges to the desired level within a finite time interval, which is critical for time-critical applications. Numerical simulation demonstrates the efficiency of the proposed cooperation control method through four collaborative transportation scenarios., Comment: 14 pages, 9 figures. This is a preprint of an article submitted for consideration in IEEE Transactions on Robotics

Digital human models of motion sickness have been actively developed, among which models based on subjective vertical conflict (SVC) theory are the most actively studied. These models facilitate the prediction of motion sickness in various scenarios such as riding in a car. Most SVC theory models predict the motion sickness incidence (MSI), which is defined as the percentage of people who would vomit with the given specific motion stimulus. However, no model has been developed to describe milder forms of discomfort or specific symptoms of motion sickness, even though predicting milder symptoms is important for applications in automobiles and daily use vehicles. Therefore, the purpose of this study was to build a computational model of symptom progression of vestibular motion sickness based on SVC theory. We focused on a model of vestibular motion sickness with six degrees-of-freedom (6DoF) head motions. The model was developed by updating the output part of the state-of-the-art SVC model, termed the 6DoF-SVC (IN1) model, from MSI to the MIsery SCale (MISC), which is a subjective rating scale for symptom progression. We conducted an experiment to measure the progression of motion sickness during a straight fore-aft motion. It was demonstrated that our proposed method, with the parameters of the output parts optimized by the experimental results, fits well with the observed MISC.

Level 3 automated driving systems (ADS) have attracted significant attention and are being commercialized. A Level 3 ADS prompts the driver to take control by requesting to intervene (RtI) when its operational design domain (ODD) or system limitations are exceeded. However, complex traffic situations may lead drivers to perceive multiple potential triggers of RtI simultaneously, causing hesitation or confusion during take-over. Therefore, drivers must clearly understand the ADS's system limitations to understand the triggers of RtI and ensure safe take-over. In this study, we propose a voice-based HMI for providing RtI trigger cues to help drivers understand ADS's system limitations. The results of a between-group experiment using a driving simulator showed that incorporating effective trigger cues into the RtI enabled drivers to comprehend the ADS's system limitations better and reduce collisions. It also improved the subjective evaluations of drivers, such as the comprehensibility of system limitations, hesitation in response to RtI, and acceptance of ADS behaviors when encountering RtI while using the ADS. Therefore, enhanced comprehension resulting from trigger cues is essential for promoting a safer and better user experience using ADS during RtI.

Autonomous Personal Mobility Vehicle (APMV) is a miniaturized autonomous vehicle designed to provide short-distance mobility to everyone in pedestrian-rich environments. By the characteristic of the open design, passengers on the APMV are exposed to the communication between the eHMI deployed on APMVs and pedestrians. Therefore, to ensure an optimal passenger experience, eHMI designs for APMVs must consider the potential impact of APMV-pedestrian communications on passengers' subjective feelings. To this end, this study discussed three external human-machine interface (eHMI) designs, i.e., 1) graphical user interface (GUI)-based eHMI with text message (eHMI-T), 2) multimodal user interface (MUI)-based eHMI with neutral voice (eHMI-NV), and 3) MUI-based eHMI with affective voice (eHMI-AV), from the perspective of APMV passengers in the communication between APMV and pedestrians. In the riding field experiment (N=24), we found that eHMI-T may be less suitable for APMVs. This conclusion was drawn based on passengers' feedback, as they expressed an awkward feeling during the "silent time" when the eHMI-T provided information only to pedestrians but not to passengers. Additionally, these two MUI-based eHMIs with voice cues had their own advantages, i.e., eHMI-NV has an advantage in pragmatic quality, while eHMI-AV has an advantage in hedonic quality. The study also highlights the necessity of considering passengers' personalities when desig

With the advancements in automated driving, there is concern that motion sickness will increase as non-driving-related tasks increase. Therefore, techniques to reduce motion sickness have drawn much attention. Research studies have attempted to estimate motion sickness using computational models for controlling it. Among them, a computational model for estimating motion sickness incidence (MSI) with visual information as input based on subjective vertical conflict theories was developed. In addition, some studies attempt to mitigate motion sickness by controlling visual information. In particular, it has been confirmed that motion sickness is suppressed by matching head movement and visual information. However, there has been no research on optimal visual information control that suppresses motion sickness in vehicles by utilizing mathematical models. We, therefore, propose a method for generating optimal visual information to suppress motion sickness caused from vehicle motion by utilizing a motion sickness model with vestibular and visual inputs. To confirm the effectiveness of the proposed method, we investigated changes in the motion sickness experienced by the participants according to the visual information displayed on the head-mounted display. The experimental results suggested that the proposed method mitigates the motion sickness of the participants.

Passengers of level 3-5 autonomous personal mobility vehicles (APMV) can perform non-driving tasks, such as reading books and smartphones, while driving. It has been pointed out that such activities may increase motion sickness, especially when frequently avoiding pedestrians or obstacles in shared spaces. Many studies have been conducted to build countermeasures, of which various computational motion sickness models have been developed. Among them, models based on subjective vertical conflict (SVC) theory, which describes vertical changes in direction sensed by human sensory organs v.s. those expected by the central nervous system, have been actively developed. However, no current computational model can integrate visual vertical information with vestibular sensations. We proposed a 6 DoF SVC-VV model which added a visually perceived vertical block into a conventional 6 DoF SVC model to predict visual vertical directions from image data simulating the visual input of a human. In a driving experiment, 27 participants experienced an APMV with two visual conditions: looking ahead (LAD) and working with a tablet device (WAD). We verified that passengers got motion sickness while riding the APMV, and the symptom were severer when especially working on it, by simulating the frequent pedestrian avoidance scenarios of the APMV in the experiment. In addition, the results of the experiment demonstrated that the proposed 6 DoF SVC-VV model could describe the increased motion sickness experienced when the visual vertical and gravitational acceleration directions were different.

Remotely operated vehicles (ROVs) have drawn much attention to underwater tasks, such as the inspection and maintenance of infrastructure. The workload of ROV operators tends to be high, even for the skilled ones. Therefore, assistance methods for the operators are desired. This study focuses on a task in which a human operator controls an underwater robot to follow a certain path while visually inspecting objects in the vicinity of the path. In such a task, it is desirable to realize the speed of trajectory control manually because the visual inspection is performed by a human operator. However, to allocate resources to visual inspection, it is desirable to minimize the workload on the path-following by assisting with the automatic control. Therefore, the objective of this study was to develop a cooperative path-following control method that achieves the above-mentioned task by expanding a robust path-following control law of nonholonomic wheeled vehicles. To simplify this problem, we considered a path-following and visual objects recognition task in a two-dimensional plane. We conducted an experiment with participants (n=16) who completed the task using the proposed method and manual control. The results showed that both the path-following errors and the workload of the participants were significantly smaller with the proposed method than with manual control. In addition, subjective responses demonstrated that operator attention tended to be allocated to objects recognition rather than robot operation tasks with the proposed method. These results indicate the effectiveness of the proposed cooperative path-following control method., Comment: 8 pages, 11figures

Passengers (drivers) of level 3-5 autonomous personal mobility vehicles (APMV) and cars can perform non-driving tasks, such as reading books and smartphones, while driving. It has been pointed out that such activities may increase motion sickness. Many studies have been conducted to build countermeasures, of which various computational motion sickness models have been developed. Many of these are based on subjective vertical conflict (SVC) theory, which describes vertical changes in direction sensed by human sensory organs vs. those expected by the central nervous system. Such models are expected to be applied to autonomous driving scenarios. However, no current computational model can integrate visual vertical information with vestibular sensations. We proposed a 6 DoF SVC-VV model which add a visually perceived vertical block into a conventional six-degrees-of-freedom SVC model to predict VV directions from image data simulating the visual input of a human. Hence, a simple image-based VV estimation method is proposed. As the validation of the proposed model, this paper focuses on describing the fact that the motion sickness increases as a passenger reads a book while using an AMPV, assuming that visual vertical (VV) plays an important role. In the static experiment, it is demonstrated that the estimated VV by the proposed method accurately described the gravitational acceleration direction with a low mean absolute deviation. In addition, the results of the driving experiment using an APMV demonstrated that the proposed 6 DoF SVC-VV model could describe that the increased motion sickness experienced when the VV and gravitational acceleration directions were different., Comment: https://www.researchgate.net/publication/358703507 Accepted as a Contributed Paper by IEEE IV2022

For assembly tasks, it is essential to firmly fix target parts and to accurately estimate their poses. Several rigid jigs for individual parts are frequently used in assembly factories to achieve precise and time-efficient product assembly. However, providing customized jigs is time-consuming. In this study, to address the lack of versatility in the shapes the jigs can be used for, we developed a flexible jig with a soft membrane including transparent beads and oil with a tuned refractive index. The bead-based jamming transition was accomplished by discharging only oil enabling a part to be firmly fixed. Because the two cameras under the jig are able to capture membrane shape changes, we proposed a sensing method to estimate the orientation of the part based on the behaviors of markers created on the jig's inner surface. Through estimation experiments, the proposed system could estimate the orientation of a cylindrical object with a diameter larger than 50 mm and an RMSE of less than 3 degrees., Comment: 6 pages, 14 figures

The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to describe the effect of the predictability of dynamics or the pattern of motion stimuli on motion sickness. In the proposed model, a submodel, in which a recursive Gaussian process regression is used to represent human features of online learning and future prediction of motion dynamics, is combined with a conventional model of motion sickness based on an observer theory. A simulation experiment was conducted in which the proposed model predicted motion sickness caused by a 900 s horizontal movement. The movement was composed of a 9 m repetitive back-and-forth movement pattern with a pause. Regarding the motion condition, the direction and timing of the motion were varied as follows: a) Predictable motion (M_P): the direction of the motion and duration of the pause were set to 8 s; b) Motion with unpredicted direction (M_dU): the pause duration was fixed as in (P), but the motion direction was randomly determined; c) Motion with unpredicted timing (M_tU): the motion direction was fixed as in (M_P), but the pause duration was randomly selected from 4 to 12 s. The results obtained using the proposed model demonstrated that the predicted motion sickness incidence for (M_P) was smaller than those for (M_dU) and (M_tU). This tendency agrees with the sickness patterns observed in a previous experimental study in which the human participants were subject to motion conditions similar to those used in our simulations. Moreover, no significant differences were found in the predicted motion sickness incidences at different conditions when the conventional model was used., Comment: Author manuscript, provisionally accepted for publication, in Frontiers in Systems Neuroscience

Advanced driver assistance systems have successfully reduced drivers' workloads and increased safety. On the other hand, the excessive use of such systems can impede the development of driving skills. However, there exist collaborative driver assistance systems, including shared and cooperative controls, which can promote effective collaboration between an assistance system and a human operator under appropriate system settings. Given an effective collaboration setup, we address the goal of simultaneously developing or maintaining driving skills while reducing workload. As there has been a paucity of research on such systems and their methodologies, we discuss a methodology applying shared and cooperative controls by considering related concepts in the skill training field. Reverse parking assisted by haptic shared control is presented as a means of increasing performance during assistance, while skill improvement following assistance is used to demonstrate the possibility of simultaneous achievement of driver assistance through the reduction of workload and skill improvement., Comment: Accepted for Cognition, Technology & Work (2018)

This study examined the effect of passengers' active head-tilt and eyes-open/closed conditions on the severity of motion sickness in the lateral acceleration environment of cars. In the centrifugal head-tilt condition, participants intentionally tilted their heads towards the centrifugal force, whereas in the centripetal head-tilt condition, the participants tilted their heads against the centrifugal acceleration. The eyes-open and eyes-closed cases were investigated for each head-tilt condition. In the experimental runs, the sickness rating in the centripetal head-tilt condition was significantly lower than that in the centrifugal head-tilt condition. Moreover, the sickness rating in the eyes-open condition was significantly lower than that in the eyes-closed condition. The results suggest that an active head-tilt motion against the centrifugal acceleration reduces the severity of motion sickness both in the eyes-open and eyes-closed conditions. They also demonstrate that the eyes-open condition significantly reduces the motion sickness even when the head-tilt strategy is used.

Previous research has shown that the effective use of inertial motion (i.e., less or no torque input at the knee joint) plays an important role in achieving a smooth gait of transfemoral prostheses in the swing phase. In our previous research, a method for generating a timed knee trajectory close to able-bodied individuals, which leads to sufficient clearance between the foot and the floor and the knee extension, was proposed using the inertial motion. Limb motions are known to correlate with each other during walking. This phenomenon is called kinematic synergy. In the present study, we measure gaits in level walking of able-bodied individuals with a wide range of walking velocities. We show that this kinematic synergy also exists between the motions of the intact limbs and those of the knee as determined by the inertial motion technique. We then propose a new method for generating the motion of the knee joint using its inertial motion close to the able-bodied individuals in mid-swing based on its kinematic synergy, such that the method can adapt to the changes in the motion velocity. The numerical simulation results show that the proposed method achieves prosthetic walking similar to that of able-bodied individuals with a wide range of constant walking velocities and termination of walking from steady-state walking. Further investigations have found that a kinematic synergy also exists at the start of walking. Overall, our method successfully achieves knee motion generation from the initiation of walking through steady-state walking with different velocities until termination of walking.

It is known that car drivers tilt their head toward the center of a curve. In addition, drivers are generally less susceptible to carsickness than are the passengers. This paper uses a mathematical model to investigate the effect of the head-tilt strategy on motion sickness. It is shown that tilting the head in the centripetal direction reduces the estimated motion sickness incidence (MSI), defined as the percentage of subjects who vomited. In addition, the head movements of both drivers and passengers were measured in a real car. It is also shown that the estimated MSI of the drivers is smaller than that of the passengers. Experimental results presented in previous studies demonstrated that the severity of motion sickness was reduced when passengers imitated the head tilt of the driver. These results strongly suggest that the driver's head tilt reduces motion sickness, and this can be understood as a subjective vertical conflict.

Objective: We investigated the effect of the passenger head-tilt strategy on the severity of carsickness in lateral acceleration situations in automobiles. Background: It is well known that the driver is generally less susceptible to carsickness than are the passengers. However, it is also known that the driver tilts his or her head toward the curve center when negotiating a curve, whereas the passenger's head moves in the opposite direction. Therefore, we hypothesized that the head-tilt strategy has the effect of reducing the severity of carsickness. Method: A passenger car was driven on a quasi-oval track with a pylon slalom while the participant sat in the navigator seat. The experiment was terminated when either the participant felt the initial symptoms of motion sickness or the car finished 20 laps. In the natural head-tilt condition, the participants were instructed to sit naturally, to relax, and not to oppose the lateral acceleration intentionally. In the active head-tilt condition, the participants were asked to tilt their heads against the centrifugal acceleration, thus imitating the driver's head tilt. Results: The number of laps achieved in the active condition was significantly greater than that in the natural condition. In addition, the subjective ratings of motion sickness and symptoms in the active condition were significantly lower than those in the natural condition. Conclusion: We suggest that an active head tilt against centrifugal acceleration reduces the severity of motion sickness. Application: Potential applications of this study include development of a methodology to reduce carsickness.

Haptic shared control is expected to achieve a smooth collaboration between humans and automated systems, because haptics facilitate mutual communication. A methodology for sharing a given task is important to achieve effective shared control. Therefore, the appropriate cooperative relationship between a human operator and automated system should be considered. This paper proposes a methodology to evaluate the cooperative status between the operator and the automated system in the haptic shared control of a steering operation using a pseudo-power pair of torque from each agent and the vehicle lateral velocity as each agent's contribution to vehicle motion. This method allows us to estimate cooperative status based on two axes: the initiative holder and the intent consistency between the two agents. A control method for a lane-keeping assist system (LKAS) that enables drivers to change lanes smoothly is proposed based on the estimated cooperative status. A gain-tuning control method based on the estimated cooperative status is proposed to decrease the assistance system's pseudo-power when intent inconsistency occurs. A method for switching the followed lane to match the driver's and assistance system's intentions is also proposed. A user study using a driving simulator is conducted to demonstrate the effectiveness of the proposed methods. The results demonstrate that the proposed methods facilitate smooth driver-initiated lane changes without significantly affecting the driver's torque or steering wheel angle while significantly improve lane-keeping performance., Comment: Accepted for International Journal of Human Robot Interaction

A mathematical model of motion sickness incidence (MSI) is derived by integrating neurophysiological knowledge of the vestibular system to predict the severity of motion sickness of humans. Bos et al. proposed the successful mathematical model of motion sickness based on the neurophysiological mechanism based on the subject vertical conflict (SVC) theory. We expand this model to 6-DOF motion, including head rotation, by introducing the otolith-canal interaction. Then the model is applied to an analysis of passengers' comfort. It is known that the driver is less susceptible to motion sickness than are the passengers. In addition, it is known that the driver tilts his/her head toward the curve direction when curve driving, whereas the passengers' head movement is likely to occur in the opposite direction. Thus, the effect of the head tilt strategy on motion sickness was investigated by the proposed mathematical model. The head movements of drivers and passengers were measured in slalom driving. Then, the MSI of the drivers and that of the passengers predicted by the proposed model were compared. The results revealed that the head movement toward the centripetal direction has a significant effect in reducing the MSI in the sense of SVC theory., Comment: in International Digital Human Modeling Symposium, 2013

We investigate the dose and dose-rate dependence of the mutation frequency caused by artificial radiations with Whack-A-Mole (WAM) model which we have recently proposed. In particular, we pay special attention to the case of long-term and low dose-rate exposure. The results indicate that the dose-rate dependence is successfully described with WAM model and it may replace the so-called DDREF, the concept of which has long been adopted to take account of the difference between the high dose-rate data and the low dose-rate ones. Basic properties of WAM model are discussed emphasizing the dose-rate dependence to demonstrate how the explicit dose-rate dependence built in the model plays a key role. By adopting the parameters that are determined to fit the mega mouse experiments, biological effects of long-term exposure to extremely low dose-rate radiation are discussed. In WAM model, the effects of the long-term exposure show a saturation property, which makes a clear distinction from the LNT hypothesis which predicts a linear increase of the effects with time., Comment: 20 pages, 5 figures, 2 tables, submitted to Journal of Nuclear Science and Technology

We present a novel model to estimate biological effects caused by artificial radiation exposure, Whack-a-mole (WAM) model. It is important to take account of the recovery effects during the time course of the cellular reactions. The inclusion of the dose-rate dependence is essential in the risk estimation of low dose radiation, while nearly all the existing theoretical models relies on the total dose dependence only. By analyzing the experimental data of the relation between the radiation dose and the induced mutation frequency of 5 organisms, mouse, drosophila, chrysanthemum, maize and tradescantia, we found that all the data can be reproduced by WAM model. Most remarkably, a scaling function, which is derived from WAM model, consistently accounts for the observed mutation frequencies of 5 organisms. This is the first rationale to account for the dose rate dependence as well as to give a unified understanding of a general feature of organisms., Comment: 26 pages, 4 figures, 1 table, Journal of the Physical Society of Japan accepted