M. Lauri, D. Hsu, and J. Pajarinen. Partially observable Markov decision processes in robotics: A survey. IEEE Trans. on Robotics, 39(1):21-40, 2023.
BibTeX  PDF

P.P. Cai, Y.F. Luo, D. Hsu, and W.S. Lee. HyP-DESPOT: A hybrid parallel algorithm for online planning under uncertainty. Int. J. Robotics Research, 40(2–3), 2021.
BibTeX  PDF

Y. Lee, P. Cai, and D. Hsu. MAGIC: Learning macro-actions for online POMDP planning.  In Proc. Robotics: Science & Systems, 2021.
BibTeX  PDF  Video

Y.F. Luo, H.Y. Bai, D. Hsu, and W.S. Lee. Importance sampling for online planning under uncertainty. Int. J. Robotics Research, 38(2–3):162–181, 2019.
BibTeX  PDF

N.P. Garg, D. Hsu, and W.S. Lee. DESPOT-α: Online POMDP planning with large state and observation spaces. In Proc. Robotics: Science & Systems, 2019.
BibTeX  PDF

P.P. Cai, Y.F. Luo, D. Hsu, and W.S. Lee. HyP-DESPOT: A hybrid parallel algorithm for online planning under uncertaintyIn Proc. Robotics: Science & Systems, 2018.
BibTeX  PDF

N. Ye, A. Somani, D. Hsu, and W. Lee. DESPOT: Online POMDP planning with regularization. J. Artificial Intelligence Research, 58:231–266, 2017.
BibTeX  PDF

Y.F. Luo, H.Y. Bai, D. Hsu, and W.S. Lee. Importance sampling for online planning under uncertainty. In Algorithmic Foundations of Robotics XII – Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2016.
BibTeX  PDF

M. Chen, E. Frazzoli, D. Hsu, and W.S. Lee. POMDP-Lite for robust planning under uncertainty. In Proc. IEEE Int. Conf. on Robotics & Automation, 2016.
BibTeX  PDF

Z. Zhang, D. Hsu, W.S. Lee, Z.W. Lim, and A. Bai. PLEASE: Palm leaf search for POMDPs with large observation spaces. In Proc. Int. Conf. on Automated Planning & Scheduling, 2015.
BibTeX  PDF

Z. Zhang, D. Hsu, and L.S. Lee. Covering number for efficient heuristic-based POMDP planning. In Proc. Int. Conf. on Machine Learning. 2014.
BibTeX PDF

H.Y. Bai, D. Hsu, and W.S. Lee. Integrated perception and planning in the continuous space: A POMDP approachInt. J. Robotics Research, 33(9):1288–1302, 2014.
BibTeX PDF

H.Y. Bai, D. Hsu, and W.S. Lee. Integrated perception and planning in the continuous space: A POMDP approach. In Proc. Robotics: Science and Systems, 2013.
BibTeX PDF (with supplementary material)

A. Somani, N. Ye, D. Hsu, and W.S. Lee. DESPOT: Online POMDP planning with regularization. In Advances in Neural Information Processing Systems (NIPS). 2013.
BibTeX PDF (with supplementary material)  Software  Video

H. Kurniawati and Y. Du and D. Hsu and W.S. Lee. Motion planning under uncertainty for robotic tasks with long time horizonsInt. J. Robotics Research, 30(3):308-323, 2011.
BibTeX  PDF

Z.W. Lim, D. Hsu, and W.S. Lee. Monte Carlo value iteration with macro-actions. In Advances in Neural Information Processing Systems (NIPS), 2011.
BibTeX  PDF  (with supplementary material)  Software

S.C.W. Ong, S.W. Png, D. Hsu, and W.S. Lee. Planning under Uncertainty for Robotic Tasks with Mixed ObservabilityInt. J. Robotics Research, 29(8):1053–1068, 2010.
BibTeX  PDF  Software

H.Y. Bai and D. Hsu and W.S. Lee and V.A. Ngo. Monte Carlo value iteration for continuous-state POMDPs. In D. Hsu et al., editors, Algorithmic Foundations of Robotics IX—Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2010.
BibTeX  PDF  Software

S.C.W. Ong, S.W. Png, D. Hsu, and W.S. Lee. POMDPs for robotic tasks with mixed observability. In Proc. Robotics: Science and Systems, 2009.
BibTeX  PDF  Software

H. Kurniawati, Y. Du, D. Hsu, and W.S. Lee. Motion planning under uncertainty for robotic tasks with long time horizons. In Proc. Int. Symp. on Robotics Research, 2009.
BibTeX PDF

D. Hsu, W.S. Lee, and N. Rong. What makes some POMDP problems easy to approximate?In Advances in Neural Information Processing Systems (NIPS), 2007.
BibTeX PDF

H. Kurniawati, D. Hsu, and W.S. Lee. SARSOP: Efficient point-based POMDP planning by approximating optimally reachable belief spaces. In Proc. Robotics: Science and Systems, 2008.
BibTeX PDF  Software

D. Hsu, W.S. Lee, and N. Rong. Accelerating point-based POMDP algorithms through successive approximations of the optimal reachable space. Technical Report TRA4/07, National University of Singapore. School of Computing, 2007.
BibTeX  PDF