arXiv subjects

Taehei Kim

Publications and source records attributed to Taehei Kim.

3 recordsLinked to original sources

arXiv2022

Sense of Embodiment Inducement for People with Reduced Lower-body Mobility and Sensations with Partial-Visuomotor Stimulation

To induce the Sense of Embodiment~(SoE) on the virtual 3D avatar during a Virtual Reality~(VR) walking scenario, VR interfaces have employed the visuotactile or visuomotor approaches. However, people with reduced lower-body mobility and sensation~(PRLMS) who are incapable of feeling or moving their legs would find this task extremely challenging. Here, we propose an upper-body motion tracking-based partial-visuomotor technique to induce SoE and positive feedback for PRLMS patients. We design partial-visuomotor stimulation consisting of two distinctive inputs~(\textit{Button Control} \& \textit{Upper Motion tracking}) and outputs~(\textit{wheelchair motion} \& \textit{Gait Motion}). The preliminary user study was conducted to explore subjective preference with qualitative feedback. From the qualitative study result, we observed the positive response on the partial-visuomotor regarding SoE in the asynchronous VR experience for PRLMS.

cs.HC↗

arXiv2022

Visual Guidance for User Placement in Avatar-Mediated Telepresence between Dissimilar Spaces

Rapid advances in technology gradually realize immersive mixed-reality (MR) telepresence between distant spaces. This paper presents a novel visual guidance system for avatar-mediated telepresence, directing users to optimal placements that facilitate the clear transfer of gaze and pointing contexts through remote avatars in dissimilar spaces, where the spatial relationship between the remote avatar and the interaction targets may differ from that of the local user. Representing the spatial relationship between the user/avatar and interaction targets with angle-based interaction features, we assign recommendation scores of sampled local placements as their maximum feature similarity with remote placements. These scores are visualized as color-coded 2D sectors to inform the users of better placements for interaction with selected targets. In addition, virtual objects of the remote space are overlapped with the local space for the user to better understand the recommendations. We examine whether the proposed score measure agrees with the actual user perception of the partner's interaction context and find a score threshold for recommendation through user experiments in virtual reality (VR). A subsequent user study in VR investigates the effectiveness and perceptual overload of different combinations of visualizations. Finally, we conduct a user study in an MR telepresence scenario to evaluate the effectiveness of our method in real-world applications.

cs.HC↗

arXiv2021

Quadruped Locomotion on Non-Rigid Terrain using Reinforcement Learning

Legged robots need to be capable of walking on diverse terrain conditions. In this paper, we present a novel reinforcement learning framework for learning locomotion on non-rigid dynamic terrains. Specifically, our framework can generate quadruped locomotion on flat elastic terrain that consists of a matrix of tiles moving up and down passively when pushed by the robot's feet. A trained robot with 55cm base length can walk on terrain that can sink up to 5cm. We propose a set of observation and reward terms that enable this locomotion; in which we found that it is crucial to include the end-effector history and end-effector velocity terms into observation. We show the effectiveness of our method by training the robot with various terrain conditions.

cs.RO↗