24 accepted papers
This paper proposes a perceptual no-reference (blind) haptic quality assessment framework for predicting the Quality of Experience (QoE) in teleoperation systems with force feedback. The proposed approach employs a deep neural network that combines semantic and distortion-based channels. The semanti…
We address the problem of making 3D scenes interactive by asking: what would objects feel like if touched in a virtual environment? While neural scene representations achieve high visual realism, they fall short in modeling physical interactions, such as the vibration patterns produced when surfaces
Online mistake detection is crucial across various domains, ranging from industrial automation to educational applications, as mistakes can be corrected by the human operator after their detection due to the continuous inference on a video stream. While prior research mainly addresses procedural err…
Recently, SO(3)-equivariant methods have been explored for 3D reconstruction via Scan-to-CAD. Despite significant advancements attributed to the unique characteristics of 3D data, existing SO(3)-equivariant approaches often fall short in seamlessly integrating local and global contextual information…
Robotic assistance is a current research topic with high application value and multiple challenges. Assistive robots are used in various scenarios, such as production lines, operating tables, and elderly care. While providing effective assistance, most of the assistance tasks that current robots can…
Given its wide application in robotics, point cloud registration is a widely researched topic. Conventional methods aim to find a rotation and translation that align two point clouds in 6 degrees of freedom (DoF). However, certain tasks in robotics, such as category-level pose estimation, involve no…
Visual SLAM is an essential tool in diverse applications such as robot perception and extended reality, where feature-based methods are prevalent due to their accuracy and robustness. However, existing methods employ either hand-crafted or solely learnable point features and are thus limited by the…
Human action recognition is crucial for intelligent robots, especially in the realm of human-robot collaboration research. Recent advancements in human pose estimation algorithms have shifted the focus of action recognition towards skeleton-based models, which exhibit robustness to changes in backgr…
Human reasoning comprises the ability to understand and reason about the current action solely based on past information. To provide effective assistance in an eldercare or household environment an assistive robot or intelligent assistive system has to assess human actions correctly. Based on this p…
Planning robot motions in complex environments is a fundamental research challenge and central to the autonomy, efficiency, and ultimately adoption of robots. While often the environment is assumed to be static, real-world settings, such as assembly lines, contain complex shaped, moving obstacles an…
This paper proposes a novel Generative Adversarial Network (GAN)-based strategy to augment subjective haptic Quality of Experience (QoE) datasets for bilateral teleoperation with haptic feedback without conducting time-consuming subjective experiments. In our previous work, we proposed a multi-asses…
We propose a novel scene-robot interaction graph (SRI-Graph) that exploits the known position of a mobile manipulator for robust and accurate scene understanding. Compared to the state-of-the-art scene graph approaches, the proposed SRI-Graph captures not only the relationships between the objects,…
This work proposes a novel haptic data reduction scheme for time-delayed teleoperation by coding information as blocks. State-of-the-art (SOTA) haptic data reduction approaches are mainly sampled-based schemes. They encode haptic signals sample by sample in order to minimize the introduced coding de…
"Entropy modeling is a key component for high-performance image compression algorithms. Recent developments in autoregressive context modeling helped learning-based methods to surpass their classical counterparts. However, the performance of those models can be further improved due to the underexplo…
Pouring liquids accurately into containers is one of the most challenging tasks for robots as they are unaware of the complex fluid dynamics and the behavior of liquids when pouring. Therefore, it is not possible to formulate a generic pouring policy for real-time applications. In this paper, we pro…
Motion control and planning for the manipulator are critical components in manipulator teleoperation. Online (real-time) motion control is challenging for active obstacle avoidance and often results in fluctuating and unsafe motion. Offline motion planning, on the other hand, generates precise and s…
Teleoperation systems with haptic feedback allow a human user to remotely interact with a dangerous or inac-cessible environment, perform various tasks, and perceive the haptic feedback. To ensure system stability while maintaining the best possible quality of experience (QoE), different teleoperati…
Analytic grasp planning algorithms typically approximate compliant contacts with soft point contact models to compute grasp quality, but these models are overly conservative and do not capture the full range of grasps available. While area contact models can reduce the number of false negatives pred…
Robot grasping of deformable hollow objects such as plastic bottles and cups is challenging, as the grasp should resist disturbances while minimally deforming the object so as not to damage it or dislodge liquids. We propose minimal work as a novel grasp quality metric that combines wrench resistanc…
The acceptance of teleoperation applications like tele-driving, tele-surgery, tele-maintenance, etc., is challenged by the quality-reducing effect of end-to-end latency. Particularly, when users wear Head-Mounted Displays to enhance the immersive experience, the lag between head motion and display r…
Assessing grasp stability is essential to prevent the failure of robotic manipulation tasks due to sensory data and object uncertainties. Learning-based approaches are widely deployed to infer the success of a grasp. Typically, the underlying model used to estimate the grasp stability is trained for…
In the field of autonomous robotics, Simultaneous Localization and Mapping (SLAM) is still a challenging problem. With cheap visual sensors attracting more and more attention, various solutions to the SLAM problem using visual cues have been proposed. However, current visual SLAM systems are still c…
We present a friction model for the curved contact area between a deformable object and soft parallel gripper jaws for grasping posture estimation. We show that the assumption of a planar contact area leads to an overestimation of the frictional force and torque, which might cause the object to slip…