Related papers: RaycastGrasp: Eye-Gaze Interaction with Wearable D…
Objects we interact with and manipulate often share similar parts, such as handles, that allow us to transfer our actions flexibly due to their shared functionality. This work addresses the problem of transferring a grasp experience or a…
Despite advances in Vision-Language-Action (VLA) models, robotic manipulation struggles with fine-grained tasks because current models lack mechanisms for active visual attention allocation. Human gaze naturally encodes intent, planning,…
Perception in robot manipulation has been actively explored with the goal of advancing and integrating vision and touch for global and local feature extraction. However, it is difficult to perceive certain object internal states, and the…
Nowadays robots play an increasingly important role in our daily life. In human-centered environments, robots often encounter piles of objects, packed items, or isolated objects. Therefore, a robot must be able to grasp and manipulate…
Wearable robotic hand rehabilitation devices can allow greater freedom and flexibility than their workstation-like counterparts. However, the field is generally lacking effective methods by which the user can operate the device: such…
Robotic manipulation requires accurate perception of the environment, which poses a significant challenge due to its inherent complexity and constantly changing nature. In this context, RGB image and point-cloud observations are two…
Humans directly completing tasks in dangerous or hazardous conditions is not always possible where these tasks are increasingly be performed remotely by teleoperated robots. However, teleoperation is difficult since the operator feels a…
Effectively manipulating articulated objects in household scenarios is a crucial step toward achieving general embodied artificial intelligence. Mainstream research in 3D vision has primarily focused on manipulation through depth perception…
Augmented reality (AR) offers immersive interaction but remains inaccessible for users with motor impairments or limited dexterity due to reliance on precise input methods. This study proposes a gesture-based interaction system for AR…
Although eye-tracking technology is being integrated into more VR and MR headsets, the true potential of eye tracking in enhancing user interactions within XR settings remains relatively untapped. Presently, one of the most prevalent gaze…
High-end components that conduct complicated tasks automatically are a part of modern industrial systems. However, in order for these parts to function at the desired level, they need to be maintained by qualified experts. Solutions based…
Designing robotic assistance devices for manipulation tasks is challenging. This work is concerned with improving accuracy and usability of semi-autonomous robots, such as human operated manipulators or exoskeletons. The key insight is to…
One goal of dexterous robotic grasping is to allow robots to handle objects with the same level of flexibility and adaptability as humans. However, it remains a challenging task to generate an optimal grasping strategy for dexterous hands,…
Robotic grasping faces new challenges in human-robot-interaction scenarios. We consider the task that the robot grasps a target object designated by human's language directives. The robot not only needs to locate a target based on…
Reliably planning fingertip grasps for multi-fingered hands lies as a key challenge for many tasks including tool use, insertion, and dexterous in-hand manipulation. This task becomes even more difficult when the robot lacks an accurate…
Recent advancements in robotic grasping have led to its integration as a core module in many manipulation systems. For instance, language-driven semantic segmentation enables the grasping of any designated object or object part. However,…
Human-robot handover is a fundamental yet challenging task in human-robot interaction and collaboration. Recently, remarkable progressions have been made in human-to-robot handovers of unknown objects by using learning-based grasp…
This research report explores the role of eye gaze in human-robot interactions and proposes a learning system for detecting objects gazed at by humans using solely visual feedback. The system leverages face detection, human attention…
Robotic manipulation of unseen objects via natural language commands remains challenging. Language driven robotic grasping (LDRG) predicts stable grasp poses from natural language queries and RGB-D images. We propose MapleGrasp, a novel…
People who are blind or have low vision regularly use their hands to interact with the physical world to gain access to objects' shape, size, weight, and texture. However, many rich visual features remain inaccessible through touch alone,…