Haptic feedback is widely used to enhance realism in virtual reality (VR). Shape and softness are two common factors perceived by the users in the haptic rendering of soft objects. To integrate these factors, we propose a new handheld shape-changing device, TapeTouch, to provide various shapes and softness in real time. TapeTouch is based on a controllable shape-changing tape, which is mainly composed of four motors and a section of brass tape. We design a structure of the components to fit a portable controller and allow to flexibly adjust the shape of the brass tape. After decoding desired shapes into the signals to control the motor, we automatically reproduce varying shapes and levels of softness to the finger or palm touching the shape-changing tape. We conducted two user studies to understand the capability of TapeTouch to render shape and softness, and the results showed that TapeTouch could provide a variety of distinguishable shapes as well as multiple levels of softness. Based on the results, we performed two VR experience studies to verify that the haptic feedback from TapeTouch enhances VR realism.

The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a multi-view consistent texture image poses a major obstacle to the output quality. In this paper, we propose a novel method to enforce multi-view consistency. Our method is based on the observation that latent space in a pre-trained diffusion model is noised separately for each camera view, making it difficult to achieve multi-view consistency by directly manipulating the latent codes. Based on the celebrated Denoising Diffusion Implicit Models (DDIM) scheme, we propose to use an optimization-based color-fusion to enforce consistency and indirectly modify the latent codes by gradient back-propagation. Our method further relaxes the sequential dependency assumption among the camera views. By evaluating on a series of general 3D models, we find our simple approach improves consistency and overall quality of the generated textures as compared to competing state-of-the-arts. Our implementation is available at: https://github.com/Quantuman134/TexPainter

This article proposes a distributed passivity-based bilateral teleoperation control for optimizing the velocity/force manipulability of the coordinated remote redundant manipulators during the task execution. Following the leader–follower paradigm, the control connects a local haptic device with a leader remote manipulator and coordinates all the leader and follower remote manipulators. The approach is novel in reconciling the potential conflicts between the pose synchronization task and the manipulability optimization task for the remote manipulators by two-layer auxiliary systems. The first layer decouples the pose synchronization constraints into separable position and orientation constraints, and the second layer optimizes the manipulability under the position and orientation constraints. The approach is robust by designing smooth controls for the manipulators without knowing their dynamic parameters. Finally, the control renders the bilateral teleoperator output strictly passive for stable physical interactions with the human user and the environment. Comparative experiments verify the effectiveness of the proposed control in the presence of time-varying communication delays.

The aspect ratio of a line chart heavily influences the perception of the underlying data. Different methods explore different criteria in choosing aspect ratios, but so far, it was still unclear how to select aspect ratios appropriately for any given data. This paper provides a guideline for the user to choose aspect ratios for any input 1D curves by conducting an in-depth analysis of aspect ratio selection methods both theoretically and experimentally. By formulating several existing methods as line integrals, we explain their parameterization invariance. Moreover, we derive a new and improved aspect ratio selection method, namely the $L_{1}$-LOR (local orientation resolution), with a certain degree of parameterization invariance. Furthermore, we connect different methods, including AL (arc length based method), the banking to 45° principle, RV (resultant vector) and AS (average absolute slope), as well as $L_{1}$-LOR and AO (average absolute orientation). We verify these connections by a comparative evaluation involving various data sets, and show that the selections by RV and $L_{1}$-LOR are complementary to each other for most data. Accordingly, we propose the dual-scale banking technique that combines the strengths of RV and $L_{1}$-LOR, and demonstrate its practicability using multiple real-world data sets.

Cancer, with high morbidity and high mortality, is one of the major burdens threatening human health globally. Intervention procedures via percutaneous puncture have been widely used by physicians due to its minimally invasive surgical approach. However, traditional manual puncture intervention depends on personal experience and faces challenges in terms of precisely puncture, learning-curve, safety and efficacy. The development of puncture interventional surgery robotic (PISR) systems could alleviate the aforementioned problems to a certain extent. This paper attempts to review the current status and prospective of PISR systems for thoracic and abdominal application. In this review, the key technologies related to the robotics, including spatial registration, positioning navigation, puncture guidance feedback, respiratory motion compensation, and motion control, are discussed in detail.