28 accepted papers
Back injuries resulting from manual material handling have long constituted a prominent threat to occupational safety. While back-support exosuits offer the potential to augment human strength, their practical implementation is hindered by persistent challenges pertaining to comfort and safety. Draw…
Self-supervised learning (SSL) for point cloud pre-training has become a cornerstone for many 3D vision tasks, enabling effective learning from large-scale unannotated data. At the scene level, existing SSL methods often incorporate volume rendering into the pre-training framework, using RGB-D image…
Self-supervised learning of point cloud aims to leverage unlabeled 3D data to learn meaningful representations without reliance on manual annotations. However, current approaches face challenges such as limited data diversity and inadequate augmentation for effective feature learning. To address the…
Vision-Language-Action (VLA) models demonstrate remarkable potential for generalizable robotic manipulation. The performance of VLA models can be improved by integrating with action chunking, a critical technique for effective control. However, action chunking linearly scales up action dimensions in
Multivariate time series forecasting plays an important role in various applications ranging from meteorology study, traffic management to economics planning. In the past decades, many efforts have been made toward accurate and reliable forecasting methods development under the assumption of intact…
We consider the problem of user-adaptive 3D gaze estimation. The performance of person-independent gaze estimation is limited due to interpersonal anatomical differences. Our goal is to provide a personalized gaze estimation model specifically adapted to a target user. Previous work on user-adaptive…
"3D point cloud segmentation has received significant interest for its growing applications. However, the generalization ability of models suffers in dynamic scenarios due to the distribution shift between test and training data. To promote robustness and adaptability across diverse scenarios, test-…
The Vision Transformer (ViT) excels in accuracy when handling high-resolution images, yet it confronts the challenge of significant spatial redundancy, leading to increased computational and memory requirements. To address this, we present the Localization and Focus Vision Transformer (LF-ViT). This…
Collaborative perception is dedicated to tackling the constraints of single-agent perception, such as occlusions, based on the multiple agents' multi-view sensor inputs. However, most existing works assume an ideal condition that all agents' multi-view cameras are continuously available. In reality,…
Multivariate time series forecasting is of central importance in modern intelligent decision systems. The dynamics of multivariate time series are jointly characterized by temporal dependencies and spatial correlations. Hence, it is equally important to build the forecasting models from both perspec…
Outdoor sports pose a challenge for people with impaired vision. The demand for higher-speed mobility inspired us to develop a vision-based wearable steering assistance. To ensure broad applicability, we focused on a representative sports environment, the athletics track. Our efforts centered on imp…
Event cameras have the ability to record continuous and detailed trajectories of objects with high temporal resolution, thereby providing intuitive motion cues for optical flow estimation. Nevertheless, most existing learning-based approaches for event optical flow estimation directly remould the pa…
Offline safe reinforcement learning (RL) algorithms promise to learn policies that satisfy safety constraints directly in offline datasets without interacting with the environment. This arrangement is particularly important in scenarios with high sampling costs and potential dangers, such as autonom…
The ability of human operators in estimating the partners’ motion intention and utilizing it for collaboration brings valuable enlightenment to human-robot systems. Motivated by these observations, this letter introduces an assimilation control method that reshapes the physical interaction trajector
"Source-free Domain Adaptation (SFDA) aims to adapt a pre-trained source model to the unlabeled target domain without accessing the well-labeled source data, which is a much more practical setting due to the data privacy, security, and transmission issues. To make up for the absence of source data,…
Stereo matching is an indispensable function that enables machine vision system to obtain depth information of its environment. However, most of existing algorithms rely on conventional camera, which follows the frame-based scheme and has several shortcomings: low dynamic range, low temporal resolut…
Motion planning for autonomous racing is a challenging task due to the safety requirement while driving aggressively. Most previous solutions utilize the prior information or depend on complex dynamics modeling. Classical model-free reinforcement learning methods are based on random sampling, which
Humanoid robots can imitate human behaviour and provide interactive services to humans due to their humanoid form, especially humanoid wheeled robots that can perform more complex tasks with the additional mobility. With the development of robotics technology, humanoid robots have been used increasi
Touch-free guided hand gesture recognition for human-robot interactions plays an increasingly significant role in teleoperated surgical robot systems. Indeed, despite depth cameras provide more practical information for recognition accuracy enhancement, the instability and computational burden of de
LiDAR point cloud streams are usually sparse in time dimension, which is limited by hardware performance. Generally, the frame rates of mechanical LiDAR sensors are 10 to 20 Hz, which is much lower than other commonly used sensors like cameras. To overcome the temporal limitations of LiDAR sensors,…
This paper proposes an efficient, fully convolutional neural network to generate robotic grasps by using 300×300 depth images as input. Specifically, a residual squeeze-and-excitation network (RSEN) is introduced for deep feature extraction. Following the RSEN block, a multi-scale spatial pyramid mo…
Under-actuated bionic hands have achieved tremendous popularity in many fields because of their advantages of lightweight, budget-friendly, satisfactory flexibility, and adaptability. Except for the bionic mechanical design, various anthropomorphic control strategies have been proposed and investiga…
Cable-driven parallel robots (CDPRs) are robots with novel structures, wherein flexible cables, instead of rigid links, are employed to pull mobile platforms. This structural change enables CDPRs to not only offer potential advantages, but also introduces control challenges with regard to frictional
In this paper, a bilateral teleoperation control of a serial robot manipulator, which guarantees a Remote Center of Motion (RCM) constraint in its kinematic level, is developed. A two-layered approach based on the energy tank model is proposed to achieve haptic feedback on the end effector with a pe…
In this paper, an Internet of Things-based human-robot collaborative control scheme is developed in Robot-assisted Minimally Invasive Surgery scenario. A hierarchical operational space formulation is designed to exploit the redundancies of the 7-DoFs redundant manipulator to handle multiple operatio…
The complexity of surgical operation can be released significantly if surgical robots can learn the manipulation skills by imitation from complex tasks demonstrations such as puncture, suturing, and knotting, etc.. This paper proposes a reinforcement learning algorithm based manipulation skill trans…
Wearable robots aim to understand and capitalize on the increasingly coupled relationships between human and robots. To this end, the field of wearable robotics considers robotic systems that work either for rehabilitation purpose to provide therapy for persons seeking to recover their physical, soc
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…