47 citations · 109 across the 7 of their papers we have counts for
9 papers
Decentralization and Acceleration Enables Large-Scale Bundle Adjustment
Taosha Fan, Joseph Ortiz, Ming Hsiao +4
Scaling to arbitrarily large bundle adjustment problems requires data and compute to be distributed across multiple devices. Centralized methods in prior works are only able to sol…
Theseus: A Library for Differentiable Nonlinear Optimization
Luis Pineda, Taosha Fan, Maurizio Monge +10
We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch, providing a common framew…
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception
Joseph Ortiz, Alexander Clegg, Jing Dong +4
We present iSDF, a continual learning system for real-time signed distance field (SDF) reconstruction. Given a stream of posed depth images from a moving camera, it trains a random…
A Robot Web for Distributed Many-Device Localisation
Riku Murai, Joseph Ortiz, Sajad Saeedi +2
We show that a distributed network of robots or other devices which make measurements of each other can collaborate to globally localise via efficient ad-hoc peer to peer communica…
Incremental Abstraction in Distributed Probabilistic SLAM Graphs
Joseph Ortiz, Talfan Evans, Edgar Sucar +1
Scene graphs represent the key components of a scene in a compact and semantically rich way, but are difficult to build during incremental SLAM operation because of the challenges…
A visual introduction to Gaussian Belief Propagation
Joseph Ortiz, Talfan Evans, Andrew J. Davison
In this article, we present a visual introduction to Gaussian Belief Propagation (GBP), an approximate probabilistic inference algorithm that operates by passing messages between t…
iMAP: Implicit Mapping and Positioning in Real-Time
Edgar Sucar, Shikun Liu, Joseph Ortiz +1
We show for the first time that a multilayer perceptron (MLP) can serve as the only scene representation in a real-time SLAM system for a handheld RGB-D camera. Our network is trai…
Bundle Adjustment on a Graph Processor
Joseph Ortiz, Mark Pupilli, Stefan Leutenegger +1
Graph processors such as Graphcore's Intelligence Processing Unit (IPU) are part of the major new wave of novel computer architecture for AI, and have a general design with massive…
FutureMapping 2: Gaussian Belief Propagation for Spatial AI
Andrew J. Davison, Joseph Ortiz
We argue the case for Gaussian Belief Propagation (GBP) as a strong algorithmic framework for the distributed, generic and incremental probabilistic estimation we need in Spatial A…