41 citations · 120 across the 37 of their papers we have counts for
6 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…