24 accepted papers
In this letter, we introduce HPGS-SLAM, a real-time RGB-D SLAM system guided by hybrid point features (combining traditional and learned point features), enabling high-precision tracking and online dense mapping with photorealistic reconstruction. HPGS-SLAM consists of two main components: (1) a lig
We present a vibrotactile codec based on a convolutional neural network that is fully rate-scalable and perceptually optimized. Rate-scalability so far was a rarely addressed problem with deep learning-based codecs. This is achieved through a bit allocation algorithm that perceptually optimizes the…
Shared autonomy bridges human expertise with machine intelligence, yet existing approaches often overlook the impact of teleoperation delays. To address this gap, we propose a novel shared autonomy approach that enables robots to gradually learn from teleoperated demonstrations while adapting to net
In this work, we propose a novel pipeline for face recognition and out-of-distribution (OOD) detection using shortrange FMCW radar. The proposed system utilizes RangeDoppler and micro Range-Doppler Images. The architecture features a primary path (PP) responsible for the classification of in-distrib…
Retrieving CAD models for real-world object scans enhances object-level mapping, providing a nuanced spatial understanding crucial for precise interactions in robotics or mixed reality. Commonly, CAD model retrieval is performed by matching features learned in Euclidean space. However, learning disc…
Teleoperation with haptic feedback allows users to interact with remote environments while retaining a sense of touch. However, the stability and transparency of these systems are compromised under communication network delay. This paper presents an augmented Model-Mediated Teleoperation with 3D obj
Understanding surface material properties is crucial for enhancing indoor robot perception and indoor digital twinning. However, not all sensor modalities typically employed for this task are capable of reliably capturing detailed surface material characteristics. By analyzing the reflected RF signa…
Recent advances in simultaneous localization and mapping (SLAM) systems have significantly enhanced the process of creating 3D digital replicas of real-world environments. Numerous applications utilizing these digital twins generally necessitate object-level annotations, which are challenging to acq
We propose HAROOD as a short-range FMCW radar-based human activity classifier and out-of-distribution (OOD) detector. It aims to classify human sitting, standing, and walking activities and to detect any other moving or stationary object as OOD. We introduce a two-stage network. The first stage is t…
In action anticipation, the model predicts the next future action after a certain observation period. In long-term action anticipation, this idea is further extended to predicting multiple actions and their respective duration. Thus, in this problem setting the model should not only capture relation…
In recency, neural signed distance fields have become more popular for reconstructing 3D indoor environments. While great improvements have been made due to missing incident radiance and materials in the surface estimation, current methods cannot reconstruct high-quality surfaces. To address this is…
Temporal action segmentation is an essential task for understandingcomplex human activity sequences and identifying long-term dependencies between human actions. This is essential for effective non-verbal human-robot collaboration and robotic assistance to understand the underlying human intentions.
Out-of-distribution (OOD) detection has recently received special attention due to its critical role in safely deploying modern deep learning (DL) architectures. This work proposes a reconstruction-based multi-class OOD detector that operates on radar range doppler images (RDIs). The detector aims t…
When providing task demonstrations to a remote robot over the network via bilateral teleoperation, communication impairments are unavoidable, hindering the human operator from delivering high-quality demonstrations. Poor-quality demonstrations can negatively impact the robot's ability to learn and g
Segmenting activities in untrimmed videos remains a critical challenge to fully understand complex human activity sequences. A correct representation of temporal action relations is key for improving incorrect segmentations. We propose a self-attention-based model that refines initial segmentations…
In the emerging field of video coding for machines, video datasets with pristine video quality and high-quality annotations are required for a comprehensive evaluation. However, existing video datasets with detailed annotations are severely limited in size and video quality. Thus, current methods ha…
We propose an extension to the LiDAR Odometry and Mapping framework (LOAM) that enables reference object-based trajectory and map optimization. Our approach assumes that the location and geometry of a large reference object are known, e.g., as a CAD model from Building Information Modeling (BIM) or
Advanced wireless communication networks provide lower latency and a higher transmission rate. Although this is an enabler for many new teleoperation applications, the risk of network instability or packet drop is still unavoidable. Real-time manipulator teleoperation requires data transmission with
Real-time 6D pose estimation is a key component for autonomous indoor navigation of Unmanned Aerial Vehicles (UAVs). This letter presents a low-latency LiDAR SLAM framework based on LiDAR scan slicing and concurrent matching, called LoLa-SLAM. Our framework uses sliced point cloud data from a rotati
LiDAR-based odometry and mapping is used in many robotic applications to retrieve the robot's position in an unknown environment and allows for autonomous operation in GPS-denied (e.g., indoor) environments. With a 3D LiDAR sensor, highly accurate localization becomes possible, which enables high qu
In the field of robotics, collaborative simultaneous localization and mapping (SLAM) is still a challenging problem. The exploration of unknown large-scale environments benefits from sharing the work among multiple agents possibly equipped with different abilities, such as aerial or ground-based veh
The usability of telepresence applications is strongly affected by the communication delay between the user and the remote system. Special attention needs to be paid in case the distant scene is experienced by means of a Head Mounted Display. A high motion-to-photon latency, which describes the time
Object retrieval and classification in point cloud data are challenged by noise, irregular sampling density, and occlusion. To address this issue, we propose a point pair descriptor that is robust to noise and occlusion and achieves high retrieval accuracy. We further show how the proposed descripto
Perceptual quality for media compression algorithms is traditionally evaluated through user studies. Such studies are time consuming, laborious and expensive, slowing down the development of new signal processing algorithms. To address this problem, a number of algorithmic quality prediction methodo…