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Christopher Iliffe Sprague
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Year
Machine learning and evolutionary techniques in interplanetary trajectory design
D Izzo, CI Sprague, DV Tailor
Modeling and Optimization in Space Engineering: State of the Art and New …, 2019
742019
Improving the modularity of auv control systems using behaviour trees
CI Sprague, Ö Özkahraman, A Munafo, R Marlow, A Phillips, P Ögren
2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV), 1-6, 2018
382018
Adding neural network controllers to behavior trees without destroying performance guarantees
CI Sprague, P Ögren
2022 IEEE 61st Conference on Decision and Control (CDC), 3989-3996, 2022
212022
PointNetKL: Deep inference for GICP covariance estimation in bathymetric SLAM
I Torroba, CI Sprague, N Bore, J Folkesson
IEEE Robotics and Automation Letters 5 (3), 4078-4085, 2020
142020
A cyber-physical system for hydrobatic auvs: system integration and field demonstration
S Bhat, I Torroba, Ö Özkahraman, N Bore, CI Sprague, Y Xie, I Stenius, ...
2020 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV), 1-8, 2020
102020
Learning dynamic-objective policies from a class of optimal trajectories
CI Sprague, D Izzo, P Ögren
2020 59th IEEE Conference on Decision and Control (CDC), 597-602, 2020
6*2020
A system for autonomous seaweed farm inspection with an underwater robot
I Stenius, J Folkesson, S Bhat, CI Sprague, L Ling, Ö Özkahraman, N Bore, ...
Sensors 22 (13), 5064, 2022
52022
Continuous-time behavior trees as discontinuous dynamical systems
CI Sprague, P Ögren
IEEE Control Systems Letters 6, 1891-1896, 2021
52021
Fully-probabilistic terrain modelling and localization with stochastic variational gaussian process maps
I Torroba, CI Sprague, J Folkesson
IEEE Robotics and Automation Letters 7 (4), 8729-8736, 2022
42022
Modelling and Simulation of Autonomous CubeSats for Orbital Debris Mitigation
CI Sprague
6th International Conference on Astrodynamics Tools and Techniques, 2016
22016
Learning how to learn bathymetry
CI Sprague, P Ögren
2020 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV), 1-2, 2020
12020
Autonomous Repair of Optical Character Recognition Data through Simple Voting and Multi-Dimensional Indexing Techniques
C Sprague
12005
Behavior Trees in Robot Control Systems
P Ögren, CI Sprague
Annual Review of Control, Robotics, and Autonomous Systems 5, 81-107, 2022
2022
Efficient and Trustworthy Artificial Intelligence for Critical Robotic Systems
C Sprague
Kungliga Tekniska högskolan, 2022
2022
An Extended Convergence Result for Behavior Tree Controllers
C Sprague, P Ögren
2022
Towards intelligent trajectory optimisation in astrodynamics
CI Sprague
Rensselaer Polytechnic Institute, 2017
2017
Deep-Learning-Based Compliant Motion Control of a Pneumatically-Driven Robotic Catheter................. D. Wu, XT Ha, Y. Zhang, M. Ourak, G. Borghesan, K. Niu, F. Trauzettel …
I Torroba, CI Sprague, J Folkesson, Z Wang, FC Ojeda, A Bisulco, D Lee, ...
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Articles 1–17