19 accepted papers
While Multimodal Large Language Models (MLLMs) have achieved remarkable progress in general visual understanding, they suffer from a fundamental geometric fragility: standard visual representations often degrade rapidly under changes in viewpoint and viewing distance. Our analysis identifies that ex…
High-resolution (HR) image perception presents a key bottleneck for multimodal large language models (MLLMs). While visual search offers a promising solution, existing methods struggle with the trade-off between coverage and efficiency. Visual expert-assisted search is efficient but prone to blind s…
Existing works on reasoning segmentation either connect hidden features from a language model directly to a mask decoder or represent positions in text, which limits interpretability and semantic detail. To solve this, we present CoPRS, a Multi-modal Chain-of-Thought (MCoT)–based positional percepti…
Teleoperation via natural-language reduces operator workload and enhances safety in high-risk or remote settings. However, in dynamic remote scenes, transmission latency during bidirectional communication creates gaps between remote perceived states and operator intent, leading to command misunderst…
While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reasoning to visual perception. Current methods, such as latent query alignment, are end-to-end yet opaque "black boxes". Conversely, textual localization
Force estimation is crucial for robotics, human--machine interaction, and industrial automation. However, traditional methods are often hindered by high cost, mechanical wear, and limited accuracy in dynamic scenarios. Vision-based tactile sensing provides a promising alternative, yet existing appro…
Due to non-destructive testing (NDT) techniques being both expensive and inconvenient in dynamic detection scenarios, innovative alternatives are urgently needed to address cost-efficiency and deployment challenges. We first design TacRoller, a tactile sensor roller for automated characterization of
Existing grasp detection methods usually rely on data-driven strategies to learn grasping features from labeled data, restricting their generalization to new scenes and objects. Preliminary researches introduce domain-invariant methods which tend to simply consider single visual representations and
Reliable 6D pose estimation is crucial for robotic tasks but presents significant challenges in environments with occlusion. Recent approaches tend to directly predict pose parameters of object with deep neural networks, lacking the modeling ability of non-adjacent and complex relationships of surfa
In this study, we introduce a new soft biomimetic optical tactile sensor based on mimicking the interlocking structure of the epidermal-dermal boundary: the BioTacTip. The primary sensing unit comprises a sharp white tip surrounded by four black cover tips that when subjected to an external force em
In order to achieve higher accuracy, the complexity of grasp detection network increases accordingly with complicated model structures and tremendous parameters. Although various light-weight strategies are adopted, directly designing the compact network can be sub-optimal and difficult to strike th
In this paper, we present the TacShade: a newly designed 3D-printed soft optical tactile sensor. The sensor is developed for shape reconstruction under the inspiration of sketch drawing that uses the density of sketch lines to draw light and shadow, resulting in the creation of a 3D-view effect. Tac…
To minimize irrelevant and redundant information in tactile data and harness the dexterity of human hands. In this paper, we introduce a novel binary classification network with normalized differential convolution (NDConv) layers. Our method leverages the recent progress in visual-based tactile sens
This paper investigates data-free class-incremental learning (DFCIL) for hand gesture recognition from 3D skeleton sequences. In this class-incremental learning (CIL) setting, while incrementally registering the new classes, we do not have access to the training samples (i.e. data-free) of t…
Although existing grasp detection methods have achieved encouraging performance under well-light conditions, repetitive experiments have found that the detection performance would deteriorate drastically under low-light conditions. Although supplementary information can be provided by additional sen
The soft fingers and strategic grasping skills enable the human hands to grasp objects in a stable manner. This letter is to model human grasping skills and transfer the learned skills to robots to improve grasping quality and success rate. First, we designed a wearable tool-like parallel hand exosk
Time delay, especially varying time delay, is always an important factor affecting the stability to the human-in-the-loop system. Previous research usually focuses on the performance of the internal signal transmission part, but rarely considers the whole system with human and environmental factors
In this paper, we create a new tendon-connected multi-functional optical tactile sensor, MechTac, for object perception in the field of view (TacTip) and location of touching points in the blind area of vision (TacSide). In a multi-point touch task, the information of the TacSide and the TacTip are…
Facing the new challenges of the spacecraft developing, the concept of cellular space robot (CSR) for both space-craft system construction and on-orbit operation is presented in this paper. The system description and design principles are introduced to ensure the flexibility of the system. And dynam…