37 accepted papers
Precise position tracking and compliant interaction between robots and unstructured environments have always been a research hotspot, particularly in unknown surface tracking tasks. Traditional approaches typically rely on force sensor data to estimate surface normals, but suffer from certain estima
In this paper, we address the problem of manipulating multi-particle aggregates using a bimanual robotic system. Our approach enables the autonomous transport of dispersed particles through a series of shaping and pushing actions using robotically-controlled tools. Achieving this advanced manipulati…
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…
Accurate depth maps are essential for robotic grasping. However, transparent objects often cause depth cameras to produce missing or distorted depth due to reflection and refraction, making grasping them particularly challenging. Precise depth estimation for transparent objects is therefore crucial.
Spatio-temporal point process (STPP) data appear in many domains. A natural way to model them is to describe how the instantaneous event rate varies over space and time given the observed history which enables interpretation, interaction detection, and forecasting. Traditional parametric kernel-base…
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
It is challenging to employ a quadruped robot for real-time mapping and positioning in a large range of scenes. The significant vibration and instability of the quadruped robot during mobility, as well as the quantity of computation required to convey a wide variety of complex landscapes, result in
The development of large Vision-Language-Action (VLA) models has enhanced the robot’s ability to manipulate objects in unseen scenarios based on language instructions. While existing VLAs have demonstrated promise in various scenarios, they still struggle with effective multi-modal data feature extr
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
In this paper, we address the problem of manipulating multi- particle aggregates using a bimanual robotic system. Our approach enables the autonomous transport of dispersed particles through a series of shaping and pushing actions using robotically controlled tools. Achieving this advanced manipulat
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 contact-rich tasks such as polishing and drilling, inevitable physical interactions often lead to task deviations due to interference, typically resulting in excessive contact forces and eventual task failure. To tackle these challenges, we propose an innovative human-guided visual-impedance cont
With the growing popularity of electric vehicles, the demand for robot-based unmanned automatic charging has become both urgent and challenging. Two key challenges need to be addressed: how to efficiently locate the charging port, and how to compliantly insert the connector into the port. In this pa
Robotic hand tool use has garnered significant attention from robotics researchers, because it enhances dexterity beyond the limitations imposed by manipulators with fixed tool configurations and human-involved manual tool changes. Despite extensive research, current methodologies predominantly focu
Since its inception, impedance control has emerged as a fundamental framework for robotic interaction control. Recent advancements in geometric impedance control have demonstrated certain advantages over traditional Cartesian impedance control. However, existing geometric impedance control approache
Real-world tasks often require combinations of both discrete and rhythmic movements. However, most of current methods can only address one of them. This letter proposes a unified framework, Wavelet Movement Primitives (WMPs), which are built on Probabilistic Movement Primitives (ProMPs) integrated w
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
The growing interest in language-conditioned robot manipulation aims to develop robots capable of understanding and executing complex tasks, with the objective of enabling robots to interpret language commands and manipulate objects accordingly. While language-conditioned approaches demonstrate impr
This letter presents a new method to automatically transport objects with mobile robots via non-prehensile actions. Our proposed approach utilizes a pair of nonholonomic robots connected by a deformable tube to efficiently manipulate objects of irregular shapes toward target locations. To autonomous
Recognizing and grasping novel-category objects remains a crucial yet challenging problem in real-world robotic applications. Despite its significance, limited research has been conducted in this specific domain. To address this, we seamlessly propose a novel framework that integrates open-vocabular…
In the realm of semi-autonomous mobile robots designed for remote operation with humans, current variable autonomy approaches struggle to reconcile conflicting intents while ensuring compliance, autonomy, and safety. To address this challenge, we propose a bidirectional trust-based variable autonomy
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…
Meta-reinforcement learning enables artificial agents to learn from related training tasks and adapt to new tasks efficiently with minimal interaction data. However, most existing research is still limited to narrow task distributions that are parametric and stationary, and does not consider out-of-…
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
Suction adhesion is widely used by natural organisms for gripping irregular objects (e.g., rocks), but their artificial counterparts show less adaptation in the same situation. In addition, they can require complex sensing and control systems to function. In this paper, we present a contact-triggere
The methods based on deep learning are the mainstream of 6D object pose estimation, which mainly include direct regression and two-stage pipelines. The former are keen by many scholars at first due to their simplicity and differentiability to poses, but they usually lack in accuracy when compared wi
Grasping of objects using multi-fingered robotic hands often fails due to small uncertainties in the hand motion control and the object's pose estimation. To tackle this problem, we propose a grasping adjustment strategy based on tactile seroving. Our technique employs feedback from a sensorized mul…
In this work, we focus on improving the robot’s dexterous capability by exploiting visual sensing and adaptive force control. TeachNet, a vision-based teleoperation learning framework, is exploited to map human hand postures to a multi-fingered robot hand. We augment TeachNet, which is originally ba…
Mobile robots can complete a task in cooperation with a human partner. In this letter, a hybrid shared control method for a mobile robot with omnidirectional wheels is proposed. A human partner utilizes a six degrees of freedom haptic device and electromyography (EMG) signals sensor to control the m
For bilateral teleoperation, the haptic feedback demands the availability of accurate force information transmitted from the remote site. Nevertheless, due to the limitation of the size, the force sensor is usually attached outside of the patient's abdominal cavity for the surgical operation. Hence,
This paper proposed an adaptive neural admittance control strategy for collision avoidance in human-robot collaborative tasks. In order to ensure that the robot end-effector can avoid collisions with surroundings, robot should be operated compliantly by human within a constrained task space. An impe…
An improved human-robot collaborative control scheme is proposed in a teleoperated minimally invasive surgery scenario, based on a hierarchical operational space formulation of a seven-degree-of-freedom redundant robot. Redundancy is exploited to guarantee a remote center of motion (RCM) constraint
Visual localization is a crucial problem in mobile robotics and autonomous driving. One solution is to retrieve images with known pose from a database for the localization of query images. However, in environments with drastically varying conditions (e.g. illumination changes, seasons, occlusion, dy…
The tutor-tutee hand-in-hand teaching may be the most effective approach for a tutee to acquire new motor skills. Repetitive nature of such procedures in a group setting usually results in a high labour cost and time inefficiency. Potential solution can be utilizing robotic platforms playing the rol…
In this paper, a human robot shared control strategy is developed and tested on a Baxter robot. Using the proposed method, the human operator only needs to consider the motion of the end-effector of the manipulator, while the manipulator will avoid obstacle by itself without sacrificing the end effe…