197 citations · 292 across the 54 of their papers we have counts for
7 papers · 1 filter
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…