Christopher Iliffe Sprague

Robotics, Perception, and Learning

Teknikringen 14

Stockholm, Sweden, 114 23

Research

My research sits at the crossroads of learning-based and model-based methods. On one hand, I aim to optimise the efficacy of model-based methods using learning techniques. On the other hand, I work to ensure the reliability of learning-based methods through model-based approaches.

My core areas of interest include robotics, physical sciences, and life sciences. These fields offer a wealth of inductive biases that can enhance learning-based methods, especially in low-data environments.

Currently, I’m expanding my research horizons as a postdoctoral researcher at SciLifeLab, in collaboration with Prof. Hossein Azizpour and Prof. Arne Elofsson. I’m exploring the potential of learning-based methods in modelling molecular interactions. My areas of interest in this domain include protein-protein interactions, drug discovery, and protein folding. Despite the scarcity of data in this field, it boasts a rich supply of geometric and physical principles that can be used to enhance learning-based models.

Prior to my current role, I pursued my PhD at the KTH Royal Institute of Technology in Stockholm, Sweden, in collaboration with Prof. Petter Ögren. My doctoral research focused on crafting efficient and trustworthy AI solutions for critical robotic systems, using behaviour trees. This work underscored the importance of efficiency and safety while exploring the potential of learning-based methods to achieve these goals, all within a framework of model-based reliability.

Before embarking on my PhD journey, I obtained both my Master’s and Bachelor’s degrees at Rensselaer Polytechnic Institute in Troy, NY, USA, specialising in aerospace engineering.

News

Nov 3, 2023	Understanding How Robots Make Decisions: Behavior Trees Explained.
Oct 20, 2021	SMaRC-team shares knowledge and encourages international collaboration at Breaking the Surface (SMaRC)
Mar 18, 2020	Researchers celebrate Antarctic under ice voyages of underwater vehicle (IMAS UTAS)
Sep 16, 2019	KTH doctoral students examined shipwrecks from the 16th century (KTH)
Jul 22, 2019	A Shipwreck, 500 Years Old, Appears on the Baltic Seabed (New York Times)

Latest posts

Feb 9, 2024	Stable Flow Matching

Selected publications

Stable Autonomous Flow Matching

Christopher Iliffe Sprague, Arne Elofsson, and Hossein Azizpour

In submission, 2024

arXiv Bib

@inproceedings{sprague2024stableaf,
  title = {Stable Autonomous Flow Matching},
  author = {Sprague, Christopher Iliffe and Elofsson, Arne and Azizpour, Hossein},
  year = {2024},
  booktitle = {submission}
}

Adding neural network controllers to behavior trees without destroying performance guarantees

Christopher Iliffe Sprague, and Petter Ögren

In 2022 IEEE 61st Conference on Decision and Control (CDC), 2022

arXiv Bib HTML

@inproceedings{sprague2022adding,
  title = {Adding neural network controllers to behavior trees without destroying performance guarantees},
  author = {Sprague, Christopher Iliffe and {\"O}gren, Petter},
  booktitle = {2022 IEEE 61st Conference on Decision and Control (CDC)},
  pages = {3989--3996},
  year = {2022},
  organization = {IEEE},
}

PointNetKL: Deep inference for GICP covariance estimation in bathymetric SLAM

Ignacio Torroba, Christopher Iliffe Sprague, Nils Bore, and John Folkesson

IEEE Robotics and Automation Letters, 2020

arXiv Bib HTML

@article{torroba2020pointnetkl,
  title = {PointNetKL: Deep inference for GICP covariance estimation in bathymetric SLAM},
  author = {Torroba, Ignacio and Sprague, Christopher Iliffe and Bore, Nils and Folkesson, John},
  journal = {IEEE Robotics and Automation Letters},
  volume = {5},
  number = {3},
  pages = {4078--4085},
  year = {2020},
  publisher = {IEEE},
}

Learning dynamic-objective policies from a class of optimal trajectories

Christopher Iliffe Sprague, Dario Izzo, and Petter Ögren

In 2020 59th IEEE Conference on Decision and Control (CDC), 2020

arXiv Bib HTML

@inproceedings{sprague2020learninh,
  title = {Learning dynamic-objective policies from a class of optimal trajectories},
  author = {Sprague, Christopher Iliffe and Izzo, Dario and {\"O}gren, Petter},
  booktitle = {2020 59th IEEE Conference on Decision and Control (CDC)},
  pages = {597--602},
  year = {2020},
  organization = {IEEE},
}

Continuous-time behavior trees as discontinuous dynamical systems

Christopher Iliffe Sprague, and Petter Ögren

IEEE Control Systems Letters, 2021

arXiv Bib HTML

@article{sprague2021continuous,
  title = {Continuous-time behavior trees as discontinuous dynamical systems},
  author = {Sprague, Christopher Iliffe and {\"O}gren, Petter},
  journal = {IEEE Control Systems Letters},
  volume = {6},
  pages = {1891--1896},
  year = {2021},
  publisher = {IEEE},
}

An Extended Convergence Result for Behavior Tree Controllers

Christopher Iliffe Sprague, and Petter Ögren

In submission, 2023

Bib HTML

@article{sprague2022extended,
  title = {An Extended Convergence Result for Behavior Tree Controllers},
  author = {Sprague, Christopher Iliffe and {\"O}gren, Petter},
  year = {2023},
  journal = {In submission},
}