20 accepted papers
Cutaneous tactile feedback is essential for robotic manipulation, particularly when interacting with deformable objects with limited visual sensing. Learning-based approaches are increasingly adopted but rely on large volumes of tactile data. To meet this demand, Sim-to-Real strategies are widely us
Embodied intelligence for contact-rich manipulation has predominantly relied on position control, while explicit awareness and regulation of interaction forces remain under-explored, limiting stability, precision, and robustness in real-world tasks. We propose ForceVLA2, an end-to-end vision-languag
Enabling robots with contact-rich manipulation remains a pivotal challenge in robot learning, which is substantially hindered by the data collection gap, including its inefficiency and limited sensor setup. While prior work has explored handheld paradigms, their rod-based mechanical structures remai…
Recent progress in vision–language–action (VLA) models has demonstrated strong potential for dual-arm manipulation, enabling complex behaviors and generalization to unseen environments. However, mainstream bimanual VLA formulations largely overlook the critical challenge of combinatorial diversity. …
Suckers are significant for robots in picking, transferring, manipulation and locomotion on diverse surfaces. However, conventional suckers lack high-fidelity tactile perception, which impedes them from resolving the fine-grained geometric features and interaction status of the target surface. This …
We present EventUPS, the first uncalibrated photometric stereo (UPS) method using an event camera--a neuromorphic sensor that asynchronously detects brightness changes with microsecond resolution. Traditional frame-based UPS methods are hindered by high bandwidth demands and limited use in dynamic s…
Vision-Language-Action (VLA) models have advanced general-purpose robotic manipulation by leveraging pretrained visual and linguistic representations. However, they struggle with contact-rich tasks that require fine-grained control involving force, especially under visual occlusion or dynamic uncert…
Anomaly detection and localization in automated industrial manufacturing can significantly enhance production efficiency and product quality. Existing methods are capable of detecting surface defects in pre-defined or controlled imaging environments. However, accurately detecting workpiece defects i
Humans can accomplish complex contact-rich tasks using vision and touch, with highly reactive capabilities such as quick adjustments to environmental changes and adaptive control of contact forces; however, this remains challenging for robots. Existing visual imitation learning (IL) approaches rely…
While humans can use parts of their arms other than the hands for manipulations like gathering and supporting, whether robots can effectively learn and perform the same type of operations remains relatively unexplored. As these manipulations require joint-level control to regulate the complete poses…
Photometric stereo faces challenges from non-Lambertian reflectance in real-world scenarios. Systematically measuring the reliability of photometric stereo methods in handling such complex reflectance necessitates a real-world dataset with quantitatively controlled reflectances. This paper introduce…
Fluid interactions are crucial in daily tasks, with properties like density and viscosity being key parameters. The property states can be used as control signals for robot operation. While density estimation is simple, assessing viscosity, especially for different fluid types, is complex. This stud…
In this work, we propose a dynamic model neural implicit embedded controller (called NEC) for high-precision tracking control of dielectric elastomer actuators (DEAs) by eliminating the rate-dependent viscoelasticity and mechanical vibration. To this end, we first establish a lumped parameter model
Photometric stereo is a well-established technique to estimate the surface normal of an object. However the requirement of capturing multiple high dynamic range images under different illumination conditions limits the speed and real-time applications. This paper introduces EventPS a novel approach…
Tactile perception stands as a critical sensory modality for human interaction with the environment. Among various tactile sensor techniques, optical sensor-based approaches have gained traction, notably for producing high-resolution tactile images. This letter explores gel elastomer deformation sim
Photometric stereo aims to recover detailed surface shapes from images captured under varying illuminations. However, existing real-world datasets primarily focus on evaluating photometric stereo for general non-Lambertian reflectances and feature bulgy shapes that have a certain height. As shape de…
This paper proposes a novel approach to conduct routine calibration for the changing mechanical parameters over time of a vision-based tactile sensor, without disassembling its overall structure, i.e., in-situ mechanical calibration. Calibration for mechanical parameters, Young's modulus and Poisson…
This work presents a novel tactile perception-based method, named T-NT, for performing the needle-threading task, an application of deformable linear object (DLO) manipulation. This task is divided into two main stages: \textit{Tail-end Finding} and \textit{Tail-end Insertion}. In the first stage, t…
Illumination planning in photometric stereo aims to find a balance between tween surface normal estimation accuracy and image capturing efficiency by selecting optimal light configurations. It depends on factors such as the unknown shape and general reflectance of the target object, global illuminat…
Evaluating photometric stereo using real-world dataset is important yet difficult. Existing datasets are insufficient due to their limited scale and random distributions in shape and material. This paper presents a new real-world photometric stereo dataset with "ground truth" normal maps, which is 1…