TouchVR: a Wearable Haptic Interface for VR Aimed at Delivering Multi-modal Stimuli at the User's Palm

TouchVR is a novel wearable haptic interface which can deliver multimodal tactile stimuli on the palm by DeltaTouch haptic display and vibrotactile feedback on the fingertips by vibration motors for the Virtual Reality (VR) user. DeltaTouch display is capable of generating 3D force vector at the contact point and presenting multimodal tactile sensation of weight, slippage, encounter, softness, and texture. The VR system consists of HTC Vive Pro base stations and head-mounted display (HMD), and Leap Motion controller for tracking the user's hands motion in VR. The MatrixTouch, BallFeel, and RoboX applications have been developed to demonstrate the capabilities of the proposed technology. A novel haptic interface can potentially bring a new level of immersion of the user in VR and make it more interactive and tangible.Comment: 2 pages, Accepted to SIGGRAPH Asia 2019 X

PolyMerge: A Novel Technique aimed at Dynamic HD Map Updates Leveraging Polylines

Currently, High-Definition (HD) maps are a prerequisite for the stable operation of autonomous vehicles. Such maps contain information about all static road objects for the vehicle to consider during navigation, such as road edges, road lanes, crosswalks, and etc. To generate such an HD map, current approaches need to process pre-recorded environment data obtained from onboard sensors. However, recording such a dataset often requires a lot of time and effort. In addition, every time actual road environments are changed, a new dataset should be recorded to generate a relevant HD map. This paper addresses a novel approach that allows to continuously generate or update the HD map using onboard sensor data. When there is no need to pre-record the dataset, updating the HD map can be run in parallel with the main autonomous vehicle navigation pipeline. The proposed approach utilizes the VectorMapNet framework to generate vector road object instances from a sensor data scan. The PolyMerge technique is aimed to merge new instances into previous ones, mitigating detection errors and, therefore, generating or updating the HD map. The performance of the algorithm was confirmed by comparison with ground truth on the NuScenes dataset. Experimental results showed that the mean error for different levels of environment complexity was comparable to the VectorMapNet single instance error.Comment: 6 pages, 9 figure

DeltaFinger: a 3-DoF Wearable Haptic Display Enabling High-Fidelity Force Vector Presentation at a User Finger

This paper presents a novel haptic device DeltaFinger designed to deliver the force of interaction with virtual objects by guiding user's finger with wearable delta mechanism. The developed interface is capable to deliver 3D force vector to the fingertip of the index finger of the user, allowing complex rendering of virtual reality (VR) environment. The developed device is able to produce the kinesthetic feedback up to 1.8 N in vertical projection and 0.9 N in horizontal projection without restricting the motion freedom of of the remaining fingers. The experimental results showed a sufficient precision in perception of force vector with DeltaFinger (mean force vector error of 0.6 rad). The proposed device potentially can be applied to VR communications, medicine, and navigation of the people with vision problems.Comment: 13 pages, 8 figures, accepted version to AsiaHaptics 202

TeslaCharge: Smart Robotic Charger Driven by Impedance Control and Human Haptic Patterns

The growing demand for electric vehicles requires the development of automated car charging methods. At the moment, the process of charging an electric car is completely manual, and that requires physical effort to accomplish the task, which is not suitable for people with disabilities. Typically, the effort in the research is focused on detecting the position and orientation of the socket, which resulted in a relatively high accuracy, $\pm 5 \: mm$ and $\pm 10^o$. However, this accuracy is not enough to complete the charging process. In this work, we focus on designing a novel methodology for robust robotic plug-in and plug-out based on human haptics, to overcome the error in the position and orientation of the socket. Participants were invited to perform the charging task, and their cognitive capabilities were recognized by measuring the applied forces along with the movement of the charger. Three controllers were designed based on impedance control to mimic the human patterns of charging an electric car. The recorded data from humans were used to calibrate the parameters of the impedance controllers: inertia $M_d$, damping $D_d$, and stiffness $K_d$. A robotic validation was performed, where the designed controllers were applied to the robot UR10. Using the proposed controllers and the human kinesthetic data, it was possible to successfully automate the operation of charging an electric car.Comment: Accepted to the 21st IEEE International Conference on Advanced Robotics (ICAR 2023). IEEE copyrigh

HaptiCharger: Robotic Charging of Electric Vehicles Based on Human Haptic Patterns

The growing demand for electric vehicles requires the development of automated car charging methods. At the moment, the process of charging an electric car is completely manual, and that requires physical effort to accomplish the task, which is not suitable for people with disabilities. Typically, the effort in the automation of the charging task research is focused on detecting the position and orientation of the socket, which resulted in a relatively high accuracy, 5 mm, and 10 degrees. However, this accuracy is not enough to complete the charging process. In this work, we focus on designing a novel methodology for robust robotic plug-in and plug-out based on human haptics to overcome the error in the orientation of the socket. Participants were invited to perform the charging task, and their cognitive capabilities were recognized by measuring the applied forces along with the movements of the charger. Eventually, an algorithm was developed based on the human's best strategies to be applied to a robotic arm.Comment: Manuscript accepted to IEEE ROBIO 202