41 citations · 120 across the 37 of their papers we have counts for
34 papers · 1 filter
Safety-aware Skill Adaptation for Reinforcement Learning in Dynamic Environments
A K M Nadimul Haque, Sheila Sutjipto, Marc G. Carmichael +1
Skill adaptation frameworks based on reinforcement learning often require restrictive assumptions to maintain stability, such as fixed observations or tightly controlled exploratio…
SplatlessDF: Continuous Distance Field Mapping with Non-Splatting Gaussians
Monisha Mushtary Uttsha, Lan Wu, Teresa Vidal-Calleja
Recent Gaussian splatting (GS) methods have shown that scenes can be represented efficiently with optimisable Gaussians for high-quality reconstruction and rendering. In this paper…
DisFlow: Scene Flow from Distance Field for Object Pose, Velocity Tracking, and Dynamic Object Reconstruction
Lan Wu, Sheila Sutjipto, Jennifer Wakulicz +1
We present \emph{DisFlow}, a novel framework for online scene flow estimation from distance field that enables \emph{6DoF dynamic object pose estimation}, \emph{motion tracking}, a…
Implicit Null-space Manifold Generation for Redundant Robotic Systems
Taiki Ishigaki, Teresa Vidal-Calleja, Ko Ayusawa +1
Robotic systems with redundant degrees of freedom can achieve the same task outcome using multiple configurations, resulting in solution sets that form manifolds in the configurati…
Towards Robot Skill Learning and Adaptation with Gaussian Processes
A K M Nadimul Haque, Fouad Sukkar, Sheila Sutjipto +4
General robot skill adaptation requires expressive representations robust to varying task configurations. While recent learning-based skill adaptation methods refined via Reinforce…
Homotopic information gain for sparse active target tracking
Jennifer Wakulicz, Ki Myung Brian Lee, Teresa Vidal-Calleja +1
The problem of planning sensing trajectories for a mobile robot to collect observations of a target and predict its future trajectory is known as active target tracking. Enabled by…
Mag-Match: Magnetic Vector Field Features for Map Matching and Registration
William McDonald, Cedric Le Gentil, Jennifer Wakulicz +1
Map matching and registration are essential tasks in robotics for localisation and integration of multi-session or multi-robot data. Traditional methods rely on cameras or LiDARs t…
Listen to Your Map: An Online Representation for Spatial Sonification
Lan Wu, Craig Jin, Monisha Mushtary Uttsha +1
Robotic perception is becoming a key technology for navigation aids, especially helping individuals with visual impairments through spatial sonification. This paper introduces a ma…
Gaussian Process Distance Fields Obstacle and Ground Constraints for Safe Navigation
Monisha Mushtary Uttsha, Cedric Le Gentil, Lan Wu +1
Navigating cluttered environments is a challenging task for any mobile system. Existing approaches for ground-based mobile systems primarily focus on small wheeled robots, which fa…
Real-Time Truly-Coupled Lidar-Inertial Motion Correction and Spatiotemporal Dynamic Object Detection
Cedric Le Gentil, Raphael Falque, Teresa Vidal-Calleja
Over the past decade, lidars have become a cornerstone of robotics state estimation and perception thanks to their ability to provide accurate geometric information about their sur…
DynORecon: Dynamic Object Reconstruction for Navigation
Yiduo Wang, Jesse Morris, Lan Wu +2
This paper presents DynORecon, a Dynamic Object Reconstruction system that leverages the information provided by Dynamic SLAM to simultaneously generate a volumetric map of observe…
Mixing Data-driven and Geometric Models for Satellite Docking Port State Estimation using an RGB or Event Camera
Cedric Le Gentil, Jack Naylor, Nuwan Munasinghe +5
In-orbit automated servicing is a promising path towards lowering the cost of satellite operations and reducing the amount of orbital debris. For this purpose, we present a pipelin…
Safe Bubble Cover for Motion Planning on Distance Fields
Ki Myung Brian Lee, Zhirui Dai, Cedric Le Gentil +3
We consider the problem of planning collision-free trajectories on distance fields. Our key observation is that querying a distance field at one configuration reveals a region of s…
VDB-GPDF: Online Gaussian Process Distance Field with VDB Structure
Lan Wu, Cedric Le Gentil, Teresa Vidal-Calleja
Robots reason about the environment through dedicated representations. Popular choices for dense representations exploit Truncated Signed Distance Functions (TSDF) and Octree data…
Interactive Distance Field Mapping and Planning to Enable Human-Robot Collaboration
Usama Ali, Lan Wu, Adrian Mueller +3
Human-robot collaborative applications require scene representations that are kept up-to-date and facilitate safe motions in dynamic scenes. In this letter, we present an interacti…
Guided Learning from Demonstration for Robust Transferability
Fouad Sukkar, Victor Hernandez Moreno, Teresa Vidal-Calleja +1
Learning from demonstration (LfD) has the potential to greatly increase the applicability of robotic manipulators in modern industrial applications. Recent progress in LfD methods…
Accurate Gaussian-Process-based Distance Fields with applications to Echolocation and Mapping
Cedric Le Gentil, Othmane-Latif Ouabi, Lan Wu +2
This paper introduces a novel method to estimate distance fields from noisy point clouds using Gaussian Process (GP) regression. Distance fields, or distance functions, gained popu…
Topological Trajectory Prediction with Homotopy Classes
Jennifer Wakulicz, Ki Myung Brian Lee, Teresa Vidal-Calleja +1
Trajectory prediction in a cluttered environment is key to many important robotics tasks such as autonomous navigation. However, there are an infinite number of possible trajectori…
Semantic keypoint extraction for scanned animals using multi-depth-camera systems
Raphael Falque, Teresa Vidal-Calleja, Alen Alempijevic
Keypoint annotation in point clouds is an important task for 3D reconstruction, object tracking and alignment, in particular in deformable or moving scenes. In the context of agric…
Continuous Planning for Inertial-Aided Systems
Mitchell Usayiwevu, Fouad Sukkar, Chanyeol Yoo +2
Inertial-aided systems require continuous motion excitation among other reasons to characterize the measurement biases that will enable accurate integration required for localizati…
Log-GPIS-MOP: A Unified Representation for Mapping, Odometry and Planning
Lan Wu, Ki Myung Brian Lee, Cedric Le Gentil +1
Whereas dedicated scene representations are required for each different task in conventional robotic systems, this paper demonstrates that a unified representation can be used dire…
Sparse Pose Graph Optimization in Cycle Space
Fang Bai, Teresa Vidal-Calleja, Giorgio Grisetti
The state-of-the-art modern pose-graph optimization (PGO) systems are vertex based. In this context the number of variables might be high, albeit the number of cycles in the graph…
Informative Planning for Worst-Case Error Minimisation in Sparse Gaussian Process Regression
Jennifer Wakulicz, Ki Myung Brian Lee, Chanyeol Yoo +2
We present a planning framework for minimising the deterministic worst-case error in sparse Gaussian process (GP) regression. We first derive a universal worst-case error bound for…
GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps
Riccardo Giubilato, Cedric Le Gentil, Mallikarjuna Vayugundla +3
Simultaneous Localization and Mapping (SLAM) techniques play a key role towards long-term autonomy of mobile robots due to the ability to correct localization errors and produce co…