20 citations · 50 across the 27 of their papers we have counts for
10 papers · 1 filter
OpenSplatGraph: From Dense Semantic Maps to Structured Scene Graphs for Open-Vocabulary Robot Perception
Binh Long Nguyen, Kien Nguyen, Clinton Fookes +1
Dense 3D mapping with semantic understanding is essential for robotic perception in complex environments. Recent 3D Gaussian Splatting-based mapping approaches enable high-fidelity…
Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation
Saimunur Rahman, Sagun Singh Shrestha, Abdelwahed Khamis +1
Automotive spinning FMCW radar provides dense, sensing and remains reliable under poor illumination and adverse weather, making it well-suited to autonomous navigation.…
NEO: NeRF It Once, Edit It Many Times for Continuous Object Manipulation
Mikołaj Zieliński, David Hall, Dominik Belter +1
In this paper, we present NEO, a unified framework providing language-guided NeRF editing for robotic manipulation. Our paper introduces (i) a language-guided object removal that c…
GemNav: Discrete-Token Visual Robot Navigation using a Multimodal Large Language Model
Peter Bohm, Saimunur Rahman, Abdelwahed Khamis +3
Visual navigation policies built on large pretrained models increasingly rely on large cross-embodiment datasets and expressive action-generation mechanisms. In this paper, we ask…
Pair-VPR: Place-Aware Pre-training and Contrastive Pair Classification for Visual Place Recognition with Vision Transformers
Stephen Hausler, Peyman Moghadam
In this work we propose a novel joint training method for Visual Place Recognition (VPR), which simultaneously learns a global descriptor and a pair classifier for re-ranking. The…
Object Registration in Neural Fields
David Hall, Stephen Hausler, Sutharsan Mahendren +1
Neural fields provide a continuous scene representation of 3D geometry and appearance in a way which has great promise for robotics applications. One functionality that unlocks uni…
Towards Long-term Robotics in the Wild
Stephen Hausler, Ethan Griffiths, Milad Ramezani +1
In this paper, we emphasise the critical importance of large-scale datasets for advancing field robotics capabilities, particularly in natural environments. While numerous datasets…
Reg-NF: Efficient Registration of Implicit Surfaces within Neural Fields
Stephen Hausler, David Hall, Sutharsan Mahendren +1
Neural fields, coordinate-based neural networks, have recently gained popularity for implicitly representing a scene. In contrast to classical methods that are based on explicit re…
WildScenes: A Benchmark for 2D and 3D Semantic Segmentation in Large-scale Natural Environments
Kavisha Vidanapathirana, Joshua Knights, Stephen Hausler +8
Recent progress in semantic scene understanding has primarily been enabled by the availability of semantically annotated bi-modal (camera and LiDAR) datasets in urban environments.…
Wild-Places: A Large-Scale Dataset for Lidar Place Recognition in Unstructured Natural Environments
Joshua Knights, Kavisha Vidanapathirana, Milad Ramezani +3
Many existing datasets for lidar place recognition are solely representative of structured urban environments, and have recently been saturated in performance by deep learning base…