6 papers
DynoJEPP: Joint Estimation, Prediction and Planning in Dynamic Environments
Mikolaj Kliniewski, Jesse Morris, Yiduo Wang +2
DynoJEPP is a factor-graph-based framework that jointly formulates and simultaneously optimizes estimation, prediction, and planning in dynamic environments. In conventional factor…
DynoSAM: Open-Source Smoothing and Mapping Framework for Dynamic SLAM
Jesse Morris, Yiduo Wang, Mikolaj Kliniewski +1
Traditional Visual Simultaneous Localization and Mapping (vSLAM) systems focus solely on static scene structures, overlooking dynamic elements in the environment. Although effectiv…
Online Dynamic SLAM with Incremental Smoothing and Mapping
Jesse Morris, Yiduo Wang, Viorela Ila
Dynamic SLAM methods jointly estimate for the static and dynamic scene components, however existing approaches, while accurate, are computationally expensive and unsuitable for onl…
Training Trajectory Predictors Without Ground-Truth Data
Mikolaj Kliniewski, Jesse Morris, Ian R. Manchester +1
This paper presents a framework capable of accurately and smoothly estimating position, heading, and velocity. Using this high-quality input, we propose a system based on Trajectro…
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…
The Importance of Coordinate Frames in Dynamic SLAM
Jesse Morris, Yiduo Wang, Viorela Ila
Most Simultaneous localisation and mapping (SLAM) systems have traditionally assumed a static world, which does not align with real-world scenarios. To enable robots to safely navi…