activity
20242026
collaborators

6 papers

cs.CV2026

HOTFLoc++: End-to-End Hierarchical LiDAR Place Recognition, Re-Ranking, and 6-DoF Metric Localisation in Forests

Ethan Griffiths, Maryam Haghighat, Simon Denman +2

This article presents HOTFLoc++, an end-to-end hierarchical framework for LiDAR place recognition, re-ranking, and 6-DoF metric localisation in forests. Leveraging an octree-based…

cs.RO2025

Vision-Guided Loco-Manipulation with a Snake Robot

Adarsh Salagame, Sasank Potluri, Keshav Bharadwaj Vaidyanathan +4

This paper presents the development and integration of a vision-guided loco-manipulation pipeline for Northeastern University's snake robot, COBRA. The system leverages a YOLOv8-ba…

cs.CV2025

HOTFormerLoc: Hierarchical Octree Transformer for Versatile Lidar Place Recognition Across Ground and Aerial Views

Ethan Griffiths, Maryam Haghighat, Simon Denman +2

We present HOTFormerLoc, a novel and versatile Hierarchical Octree-based TransFormer, for large-scale 3D place recognition in both ground-to-ground and ground-to-aerial scenarios a…

cs.RO2025

Online 6DoF Global Localisation in Forests using Semantically-Guided Re-Localisation and Cross-View Factor-Graph Optimisation

Lucas Carvalho de Lima, Ethan Griffiths, Maryam Haghighat +5

This paper presents FGLoc6D, a novel approach for robust global localisation and online 6DoF pose estimation of ground robots in forest environments by leveraging deep semantically…

cs.RO2025

Reduced-Order Model-Based Gait Generation for Snake Robot Locomotion using NMPC

Adarsh Salagame, Eric Sihite, Milad Ramezani +1

This paper presents an optimization-based motion planning methodology for snake robots operating in constrained environments. By using a reduced-order model, the proposed approach…

cs.RO2024

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.…