197 citations · 292 across the 54 of their papers we have counts for
60 papers
When to Adapt: Multi-Signal Domain Shift Detection for Efficient Training-Free Adaptation in Open-Vocabulary Segmentation
Michele Antonazzi, Alejandra C. Hernandez, José Araujo +2
Robust and reliable perception is essential for autonomous robots operating in real-world environments, particularly in long-term missions where environmental conditions may change…
Probabilistic Scene Graphs: Hierarchical Representation and Real-time System
Waqas Ali, Michele Antonazzi, Timon Homberger +4
3D scene graphs provide semantically rich and hierarchical representations for robot perception. However, existing systems do not maintain uncertainty as an explicit belief or prop…
Accelerating Large-scale Bundle Adjustment for LiDAR Mapping via Parallel Computing
Yixi Cai, Rundong Li, Yuhan Xie +3
LiDAR bundle adjustment is widely utilized in mapping to construct globally consistent point cloud maps. In this paper, we propose the first fully parallel computing framework to a…
GESTO: Human-Centric Spatio-Temporal Memory for Reasoning in Dynamic Scenes
Ermanno Bartoli, Buwei He, Dennis Rotondi +6
Robots operating in human environments need memories that capture not only what objects exist and where, but also how people use them over time and how individual interactions comp…
Risk-Aware Belief Control Barrier Functions over Random Finite Sets
Shaohang Han, Gang Chen, Yixi Cai +5
Ensuring robot safety in unknown, dynamic environments is a fundamental requirement. It involves inferring the states of an unknown and time-varying number of moving objects from n…
SynFlow: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data
Qingwen Zhang, Xiaomeng Zhu, Chenhan Jiang +1
Reliable 3D dynamic perception requires models that can anticipate motion beyond predefined categories, yet progress is hindered by the scarcity of dense, high-quality motion annot…
TeFlow: Enabling Multi-frame Supervision for Self-Supervised Feed-forward Scene Flow Estimation
Qingwen Zhang, Chenhan Jiang, Xiaomeng Zhu +4
Self-supervised feed-forward methods for scene flow estimation offer real-time efficiency, but their supervision from two-frame point correspondences is unreliable and often breaks…
Visible Structure Retrieval for Lightweight Image-Based Relocalisation
Fereidoon Zangeneh, Leonard Bruns, Amit Dekel +2
Accurate camera pose estimation from an image observation in a previously mapped environment is commonly done through structure-based methods: by finding correspondences between 2D…
BlendCLIP: Bridging Synthetic and Real Domains for Zero-Shot 3D Object Classification with Multimodal Pretraining
Ajinkya Khoche, Gergő László Nagy, Maciej Wozniak +2
Zero-shot 3D object classification is crucial for real-world applications like autonomous driving, however it is often hindered by a significant domain gap between the synthetic da…
ArgoTweak: Towards Self-Updating HD Maps through Structured Priors
Lena Wild, Rafael Valencia, Patric Jensfelt
Reliable integration of prior information is crucial for self-verifying and self-updating HD maps. However, no public dataset includes the required triplet of prior maps, current m…
Social 3D Scene Graphs: Modeling Human Actions and Relations for Interactive Service Robots
Ermanno Bartoli, Dennis Rotondi, Buwei He +3
Understanding how people interact with their surroundings and each other is essential for enabling robots to act in socially compliant and context-aware ways. While 3D Scene Graphs…
DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance
Ajinkya Khoche, Qingwen Zhang, Yixi Cai +2
Accurate 3D scene flow estimation is critical for autonomous systems to navigate dynamic environments safely, but creating the necessary large-scale, manually annotated datasets re…
DeltaFlow: An Efficient Multi-frame Scene Flow Estimation Method
Qingwen Zhang, Xiaomeng Zhu, Yushan Zhang +3
Previous dominant methods for scene flow estimation focus mainly on input from two consecutive frames, neglecting valuable information in the temporal domain. While recent trends s…
PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving
Maciej K. Wozniak, Lianhang Liu, Yixi Cai +1
While end-to-end autonomous driving models show promising results, their practical deployment is often hindered by large model sizes, a reliance on expensive LiDAR sensors and comp…
Information Gain Is Not All You Need
Ludvig Ericson, José Pedro, Patric Jensfelt
Autonomous exploration in mobile robotics often involves a trade-off between two objectives: maximizing environmental coverage and minimizing the total path length. In the widely u…
Quantifying Epistemic Uncertainty in Absolute Pose Regression
Fereidoon Zangeneh, Amit Dekel, Alessandro Pieropan +1
Visual relocalization is the task of estimating the camera pose given an image it views. Absolute pose regression offers a solution to this task by training a neural network, direc…
HiMo: High-Speed Objects Motion Compensation in Point Clouds
Qingwen Zhang, Ajinkya Khoche, Yi Yang +4
LiDAR point cloud is essential for autonomous vehicles, but motion distortions from dynamic objects degrade the data quality. While previous work has considered distortions caused…
SSF: Sparse Long-Range Scene Flow for Autonomous Driving
Ajinkya Khoche, Qingwen Zhang, Laura Pereira Sanchez +3
Scene flow enables an understanding of the motion characteristics of the environment in the 3D world. It gains particular significance in the long-range, where object-based percept…
Conditional Variational Autoencoders for Probabilistic Pose Regression
Fereidoon Zangeneh, Leonard Bruns, Amit Dekel +2
Robots rely on visual relocalization to estimate their pose from camera images when they lose track. One of the challenges in visual relocalization is repetitive structures in the…
Fusion in Context: A Multimodal Approach to Affective State Recognition
Youssef Mohamed, Severin Lemaignan, Arzu Guneysu +2
Accurate recognition of human emotions is a crucial challenge in affective computing and human-robot interaction (HRI). Emotional states play a vital role in shaping behaviors, dec…
ExelMap: Explainable Element-based HD-Map Change Detection and Update
Lena Wild, Ludvig Ericson, Rafael Valencia +1
Acquisition and maintenance are central problems in deploying high-definition (HD) maps for autonomous driving, with two lines of research prevalent in current literature: Online H…
HD-maps as Prior Information for Globally Consistent Mapping in GPS-denied Environments
Waqas Ali, Patric Jensfelt, Thien-Minh Nguyen
In recent years, prior maps have become a mainstream tool in autonomous navigation. However, commonly available prior maps are still tailored to control-and-decision tasks, and the…
SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving
Qingwen Zhang, Yi Yang, Peizheng Li +2
Scene flow estimation predicts the 3D motion at each point in successive LiDAR scans. This detailed, point-level, information can help autonomous vehicles to accurately predict and…
Beyond the Frontier: Predicting Unseen Walls from Occupancy Grids by Learning from Floor Plans
Ludvig Ericson, Patric Jensfelt
In this paper, we tackle the challenge of predicting the unseen walls of a partially observed environment as a set of 2D line segments, conditioned on occupancy grids integrated al…