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Paul H J Kelly

9 accepted papers

2024

Distributed Simultaneous Localisation and Auto-Calibration Using Gaussian Belief Propagation

RA-L 2024

We present a novel scalable, fully distributed, and online method for simultaneous localisation and extrinsic calibration for multi-robot setups. Individual a priori unknown robot poses are probabilistically inferred as robots sense each other while simultaneously calibrating their sensors and marke

Cited by 14SourceScholar
2020

BIT-VO: Visual Odometry at 300 FPS using Binary Features from the Focal Plane

IROS 2020poster

Focal-plane Sensor-processor (FPSP) is a next-generation camera technology which enables every pixel on the sensor chip to perform computation in parallel, on the focal plane where the light intensity is captured. SCAMP-5 is a general-purpose FPSP used in this work and it carries out computations in…

Cited by 16SourceScholar
2020

Scalable Uncertainty for Computer Vision With Functional Variational Inference

CVPR 2020poster

As Deep Learning continues to yield successful applications in Computer Vision, the ability to quantify all forms of uncertainty is a paramount requirement for its safe and reliable deployment in the real-world. In this work, we leverage the formulation of variational inference in function space, wh…

Cited by 26PDFScholar
2019

Characterizing Visual Localization and Mapping Datasets

ICRA 2019poster

Benchmarking mapping and motion estimation algorithms is established practice in robotics and computer vision. As the diversity of datasets increases, in terms of the trajectories, models, and scenes, it becomes a challenge to select datasets for a given benchmarking purpose. Inspired by the Wassers…

Cited by 30SourceScholar
2018

Efficient Octree-Based Volumetric SLAM Supporting Signed-Distance and Occupancy Mapping

RA-L 2018

We present a dense volumetric simultaneous localisation and mapping (SLAM) framework that uses an octree representation for efficient fusion and rendering of either a truncated signed distance field (TSDF) or an occupancy map. The primary aim of this letter is to use one single representation of the

Cited by 127SourceScholar
2018

SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM

ICRA 2018poster

SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify the interface of such algorithms, or to perform a holistic comparison of their capabilities. This is a problem since dif…

Cited by 79SourcecodeScholar
2017

Application-oriented design space exploration for SLAM algorithms

ICRA 2017poster

In visual SLAM, there are many software and hardware parameters, such as algorithmic thresholds and GPU frequency, that need to be tuned; however, this tuning should also take into account the structure and motion of the camera. In this paper, we determine the complexity of the structure and motion…

Cited by 39SourceScholar
2016

Comparative design space exploration of dense and semi-dense SLAM

ICRA 2016

SLAM has matured significantly over the past few years, and is beginning to appear in serious commercial products. While new SLAM systems are being proposed at every conference, evaluation is often restricted to qualitative visualizations or accuracy estimation against a ground truth. This is due to

Cited by 26SourceScholar
2015

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

ICRA 2015poster

Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their high computational requirements mean that use on mass market embedded platforms is challenging. Meanwhile, trends in low-c…

Cited by 211SourceScholar