Publications by Christopher Iliffe Sprague
Peer reviewed
Articles
[1]
I. Stenius et al., "A system for autonomous seaweed farm inspection with an underwater robot," Sensors, vol. 22, no. 13, 2022.
[2]
P. Ögren and C. Sprague, "Behavior Trees in Robot Control Systems," Annual Review of Control, Robotics, and Autonomous Systems, vol. 5, no. 1, pp. 81-107, 2022.
[3]
C. Sprague and P. Ögren, "Continuous-Time Behavior Trees as Discontinuous Dynamical Systems," IEEE Control Systems Letters, vol. 6, pp. 1891-1896, 2022.
[4]
I. Torroba, C. Sprague and J. Folkesson, "Fully-Probabilistic Terrain Modelling and Localization With Stochastic Variational Gaussian Process Maps," IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 8729-8736, 2022.
[5]
I. Torroba et al., "PointNetKL : Deep Inference for GICP Covariance Estimation in Bathymetric SLAM," IEEE Robotics and Automation Letters, vol. 5, no. 3, pp. 4078-4085, 2020.
Conference papers
[6]
C. Sprague and P. Ögren, "Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees," in The 61th IEEE Conference on Decision and Control (CDC 2022), 2022.
[7]
C. I. Sprague and P. Ögren, "Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees," in 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), 2022, pp. 3989-3996.
[8]
S. Bhat et al., "A Cyber-Physical System for Hydrobatic AUVs : System Integration and Field Demonstration," in 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020, 2020.
[9]
S. Bhat et al., "A Cyber-Physical System for Hydrobatic AUVs: System Integration and Field Demonstration," in IEEE OES Autonomous Underwater Vehicles Symposium, St. Johns, Newfoundland, Canada, 2020, 2020.
[10]
C. Sprague, D. Izzo and P. Ögren, "Learning Dynamic-Objective Policies from a Class of Optimal Trajectories," in Proceedings of the IEEE Conference on Decision and Control, 2020, pp. 597-602.
[11]
C. Sprague and P. Ögren, "Learning How to Learn Bathymetry," in 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020, 2020.
[12]
C. Sprague et al., "Improving the Modularity of AUV Control Systems using Behaviour Trees," in AUV 2018 - 2018 IEEE/OES Autonomous Underwater Vehicle Workshop, Proceedings, 2018.
Chapters in books
[13]
D. Izzo, C. Sprague and D. V. Tailor, "Machine Learning and Evolutionary Techniques in Interplanetary Trajectory Design," in Modeling and Optimization in Space Engineering, : Springer International Publishing, 2019, pp. 191-210.
Non-peer reviewed
Theses
[14]
C. Sprague, "Efficient and Trustworthy Artificial Intelligence for Critical Robotic Systems," Doctoral thesis Stockholm : Kungliga Tekniska högskolan, TRITA-EECS-AVL, 2022:68, 2022.
Other
[15]
C. Sprague and P. Ögren, "An Extended Convergence Result for Behavior Tree Controllers," (Manuscript).
Latest sync with DiVA:
2024-05-31 00:10:41