Publications | AdaComp

Y. Xu, J. Mao, Y. Du, T. Lozano-Perez, L.P. Kaelbling, and D. Hsu. “Set It Up!”: Functional Object Arrangement with Compositional Generative Models. In Proc. Robotics: Science & Systems, 2024.
BibTeX PDF

S. Cai, A. Ram, Z. Gou, M.A.W. Shaikh, Y.A. Chen, Y. Wan, K. Hara, S. Zhao and D. Hsu. Navigating Real-World Challenges: A Quadruped Robot Guiding System for Visually Impaired People in Diverse Environments. In Proc. ACM Conf. on Human Factors in Computing Systems, 2024.
BibTeX PDF

@inproceedings{Cai2024Nav,
author = {Cai, Shaojun and Ram, Ashwin and Gou, Zhengtai and Shaikh, Mohd Alqama Wasim and Chen, Yu-An and Wan, Yingjia and Hara, Kotaro and Zhao, Shengdong and Hsu, David},
title = {Navigating Real-World Challenges: A Quadruped Robot Guiding System for Visually Impaired People in Diverse Environments},
year = {2024},
booktitle = {Proceedings of the CHI Conference on Human Factors in Computing Systems},
}

J. Loo and D. Hsu. Scene Action Maps: Behavioural Maps for Navigation without Metric Information. In In Proc. IEEE Int. Conf. on Robotics & Automation, 2024.
BibTeX PDF

@inproceedings{Loo2024Sam, 
        author    = {Joel Loo and David Hsu}, 
        title     = {{Scene Action Maps: Behavioural Maps for Navigation without Metric Information}}, 
        booktitle = {International Conference on Robotics and Automation (ICRA)}, 
        year      = {2024},
    }

Z. Zhao, W.S. Lee, and D. Hsu. Large Language Models as commonsense knowledge for large-scale task planning. In Advances in Neural Information Processing Systems, 2023.
BibTeX PDF

@inproceedings{
Zhao23large,
title={Large Language Models as Commonsense Knowledge for Large-Scale Task Planning},
author={Zirui Zhao and Wee Sun Lee and David Hsu},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
}

P. Tran, H. Wu, C. Yu, P. Cai, S. Zheng, and D. Hsu. What truly matters in trajectory Prediction for autonomous driving? In Advances in Neural Information Processing Systems, 2023.
BibTeX PDF

@inproceedings{TranWu23what,
	author = {Phong Tran and Haoran Wu and Cunjun Yu and  Panpan Cai and Sifa Zheng and David Hsu},
	booktitle = NeurIPS,
	title = { What Truly Matters in Trajectory Prediction for Autonomous Driving?},
	year = {2023}}

Z. Zhao, W.S. Lee, and D. Hsu. Differentiable parsing and visual grounding of natural language instructions for object placement. In Proc. IEEE Int. Conf. on Robotics & Automation, 2023.
BibTeX PDF

@inproceedings{AiGao22,
	author = {Z. Zhao and W.S. Lee and D. Hsu},
	booktitle = ICRA,
	title = {Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement},
	year = {2023}}

P. Cai and D. Hsu. Closing the planning-learning loop with application to autonomous driving. IEEE Trans. on Robotics, 39(2):998–1011, 2023.
BibTeX PDF

@article{CaiHsu23,
	title = {Closing the Planning-Learning Loop with Application to Autonomous Driving},
	author = {P. Cai and D. Hsu},
	journal = TRO,
	volume = {39},
	number = {2},
	pages = {998-1011},
	year = {2023}}

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

@article{LauHsu23,
        title = {Partially Observable Markov Decision Processes in Robotics: A Survey},
        author = {M. Lauri and D. Hsu and J. Pajarinen},
        journal = TRO,
        volume = {39},
        number = {1},
        year = {2023}}

S. Chen, Y. Xu, C. Yu, L. Li, X. Ma, Z. Xu, and D. Hsu. DaXBench: Benchmarking deformable object manipulation with differentiable physics. In Proc. Int. Conf. on Learning Representations, 2023.
BibTeX PDF Code

@inproceedings{CheXu23,
	title = {DaXBench: Benchmarking Deformable Object Manipulation with Differentiable Physics},
	author = {S. Chen and Y. Xu and C. Yu and L. Li and X. Ma and Z. Xu and D. Hsu},
	booktitle = {Proc. Int. Conf. on Learning Representations},
	year = {2023}
}

M. H. Danesh, P. Cai, and D. Hsu. LEADER: Learning attention over driving behaviors for planning under uncertainty. In Proc. Conference on Robot Learning, 2022.
BibTeX PDF

@inproceedings{
danesh2022leader,
title={{LEADER}: Learning Attention over Driving Behaviors for Planning under Uncertainty},
author={Mohamad Hosein Danesh and Panpan Cai and David Hsu},
booktitle={Proc. Conference on Robot Learning},
year={2022},
}

C. Yu, Y. Xu, L. Lin, and D. Hsu. COACH: Cooperative robot teaching. In Proc. Conference on Robot Learning, 2022.
BibTeX PDF

@inproceedings{
yu2022coach,
title={{COACH}: Cooperative Robot Teaching},
author={Cunjun Yu and Yiqing Xu and Linfeng Li and David Hsu},
booktitle={Proc. Conference on Robot Learning},
year={2022},
}

Y. Xu, W. Gao, and D. Hsu. Receding horizon inverse reinforcement learning. In Advances in Neural Information Processing Systems, 2022.
BibTeX PDF

@inproceedings{
xu2022receding,
title={Receding Horizon Inverse Reinforcement Learning},
author={Yiqing Xu and Wei Gao and David Hsu},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},}

Y. Luo, P. Cai, Y. Lee, , and D. Hsu. GAMMA: A general agent motion model for autonomous driving. IEEE Robotics & Automation Letters, 7(2):3499–3506, 2022.
BibTeX PDF

@Article{LuoCai22,
	author = {Y. Luo and P. Cai and Y. Lee and and D. Hsu},
	bib2html_pubtype = {Journal},
	bib2html_rescat = {Autonomous Driving,POMDP Applications},
	journal = { IEEE Robotics \& Automation Letters},
	volume = {7},
        number={2},
        pages={3499-3506},
	title = {{GAMMA}: A General Agent Motion Model for Autonomous Driving},
	year = {2022}}

X. Ma, D. Hsu, and W.S. Lee. Learning latent graph dynamics for visual manipulation of deformable objects. In Proc. IEEE Int. Conf. on Robotics & Automation, 2022.
BibTeX PDF

@inproceedings{MaHsu22,
	author = {X. Ma  and D. Hsu and W.S. Lee},
	bib2html_pubtype = {Refereed Conference and Workshop},
	bib2html_rescat = {Deformable Object Manipulation},
	booktitle = {Proc. IEEE Int. Conf. on Robotics & Automation},
	title = {Learning Latent Graph Dynamics for Visual Manipulation of Deformable Objects},
	year = {2022}}

B. Ai, W. Gao, Vinay, and D. Hsu. Deep visual navigation under partial observability. In Proc. IEEE Int. Conf. on Robotics & Automation, 2022.
BibTeX PDF

@inproceedings{AiGao22,
	author = {B. Ai and W. Gao and Vinay and  D. Hsu},
	bib2html_pubtype = {Refereed Conference and Workshop},
	bib2html_rescat = {Deep Learning, Navigation},
	booktitle = {Proc. IEEE Int. Conf. on Robotics & Automation},
	title = {Deep Visual Navigation under Partial Observability},
	year = {2022}}

Y.F. Luo, M. Meghjani, Q.H. Ho, D. Rus, and D. Hsu. Interactive planning for autonomous urban driving in adversarial scenarios. In Proc. IEEE Int. Conf. on Robotics & Automation, 2021.
BibTeX PDF

@inproceedings{LuoMeg21,
	author = {Y.F. Luo and M. Meghjani and Q.H. Ho and D. Rus and D. Hsu},
	bib2html_pubtype = {Refereed Conference and Workshop},
	bib2html_rescat = {Autonomous Driving},
	booktitle = {Proc. IEEE Int. Conf. on Robotics \& Automation},
	title = {Interactive Planning for Autonomous Urban Driving in Adversarial Scenarios},
	year = {2021}}

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

@article{CaiLuo21,
	author = {P.P. Cai and Y.F. Luo and D. Hsu and W.S. Lee},
	bib2html_pubtype = {Journal},
	bib2html_rescat = {POMDP Planning},
	journal = {Int. J.  Robotics Research},
	number = {2--3},
	title = {{HyP-DESPOT}: A Hybrid Parallel Algorithm for Online Planning under Uncertainty},
	volume = {40},
	year = {2021}}

H. Zhang, S. Bai, X. Lan, D. Hsu, and N. Zheng. Hindsight trust region policy optimization. In Proc. Int. Jnt. Conf. on Artificial Intelligence, 2021.
BibTeX PDF

@inproceedings{ZhangBai21,
	author = {H. Zhang and S. Bai and X. Lan and D. Hsu and N. Zheng},
	bib2html_pubtype = {Refereed Conference and Workshop},
	bib2html_rescat = {Reinforcement Learning},
	booktitle ={Proc. Int. Jnt. Conf. on Artificial Intelligence},
	title = {Hindsight Trust Region Policy Optimization},
	year = {2021}}

P. Karkus, S. Cai, and D. Hsu. Differentiable SLAM-net: Learning particle SLAM for visual navigation. In Proc. IEEE Conf. on Computer Vision & Pattern Recognition, 2021.
BibTeX PDF

@inproceedings{KarCai21,
	author = {P. Karkus and S. Cai and D. Hsu},
	bib2html_pubtype = {Refereed Conference and Workshop},
	bib2html_rescat = {DAN, Integrating Planning and Learning},
	booktitle = {Proc. IEEE Conf. on Computer Vision \& Pattern Recognition},
	title = {Differentiable {SLAM}-Net: Learning Particle {SLAM} for Visual Navigation},
	year = {2021}}

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

@inproceedings{LeeCai21,
	Author = {Y. Lee and P. Cai, and D. Hsu },
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {POMDP Planning, Autonomous Driving},
	Booktitle = RSS,
	Title = {MAGIC: Learning Macro-Actions for Online POMDP Planning},
	Year = {2021}}

H. Zhang, Y. Lu, C. Yu, D. Hsu, X. Lan, and N. Zheng. INVIGORATE: Interactive visual grounding and grasping in clutter. In Proc. Robotics: Science & Systems, 2021.
BibTeX PDF Video

@inproceedings{ZhangLu21,
	Author = {H. Zhang and Y. Lu and C. Yu and D. Hsu and X. Lan and N. Zheng.},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Human-Robot Interaction, POMDP Applications},
	Booktitle = RSS,
	Title = {INVIGORATE: Interactive Visual Grounding and Grasping in Clutter},
	Year = {2021}}

S. Chen, X. Ma, Y. Lu, and D. Hsu. Ab initio particle-based object manipulation. In Proc. Robotics: Science & Systems, 2021.
BibTeX PDF Video

@inproceedings{Chen21,
	Author = {S. Chen and X. Ma and Y. Lu and D. Hsu.},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Object Manipulation},
	Booktitle = RSS,
	Title = {Ab Initio Particle-based Object Manipulation},
	Year = {2021}
}

H. Soh, Y. Xie, M. Chen, and D. Hsu. Multi-task trust transfer for human-robot interaction. Int. J. Robotics Research, 39(2–3):233–249, 2020.
BibTeX PDF

@Article{SohXie20,
	Author = {H. Soh and Y. Xie and M. Chen and D. Hsu},
	Bib2Html_Pubtype = {Journal},
	Bib2Html_Rescat = {Human-Robot Interaction, Trust-Aware Decision Making},
	Booktitle = RSS,
	Title = {Multi-Task Trust Transfer for Human-Robot Interaction},
       Journal = IJRR,
       Year = {2020},
       Volume =  {39},
       Number = {2--3},
       Pages = 	 {233--249},
}

M. Shridhar, D. Mittal, and D. Hsu. Interactive visual grounding of referring expressions for human-robot interaction. Int. J. Robotics Research, 39(2–3):217–232, 2020.
BibTeX PDF

@Article{ShrMit20,
	Author = {M. Shridhar and D. Mittal and D. Hsu},
	Bib2Html_Pubtype = {Journal},
	Bib2Html_Rescat = {Human-Robot Interaction},
	Booktitle = IJRR,
	Title = {Interactive Visual Grounding of Referring Expressions for Human-Robot Interaction},
       Journal = IJRR,
       Year = {2020},
       Volume =  {39},
       Number = {2--3},
       Pages = 	 {217--232},
}

X. Ma, P. Karkus, D. Hsu, W.S. Lee, and N. Ye. Discriminative particle filter reinforcement learning for complex partial observations. In Proc. Int. Conf. on Learning Representations, 2020.
BibTeX PDF

@InProceedings{MaKar20b,
 Bib2Html_Pubtype = {Refereed Conference and Workshop},
 Bib2Html_Rescat = {Deep Learning, Reinforcement Learning},
 Author = 	 {X. Ma and P. Karkus and D. Hsu and W.S. Lee and N. Ye},
 Title = 	 {Discriminative Particle Filter Reinforcement Learning For Complex Partial Observations},
 Booktitle = ICLR,
 Year = 	 {2020},
}

X. Ma, P. Karkus, D. Hsu, and W.S. Lee. Particle filter recurrent neural networks. In Proc. AAAI Conf. on Artificial Intelligence, 2020.
BibTeX PDF

@InProceedings{MaKar20a,
 Bib2Html_Pubtype = {Refereed Conference and Workshop},
 Bib2Html_Rescat = {Deep Learning},
 Author = 	 {X. Ma and P. Karkus and D. Hsu and W.S. Lee},
 Title = 	 {Particle Filter Recurrent Neural Networks},
 Booktitle = AAAI,
 Year = 	 {2020},
}

M. Chen, S. Nikolaidis, H. Soh, D. Hsu, and S. Srinivasa. Trust-aware decision making for human-robot collaboration: Model learning and planning. ACM Trans. on Human-Robot Interaction, 9(2):1–23, 2020.
BibTeX PDF

@article{CheNik20,
 Bib2Html_Pubtype = {Journal},
 Bib2Html_Rescat = {Human-Robot Interaction, Trust-Aware Decision Making},
 Title={Trust-Aware Decision Making for Human-Robot Collaboration: Model Learning and Planning},
 Author={Chen, M.  and Nikolaidis, S.  and Soh, H.  and Hsu, D. and Srinivasa, S.},
 Journal=THRI,
 Volume={9},
 Number={2},
 Pages={1--23},
 Year={2020},
}

P. Cai, Y. Lee, Y. Luo, and D. Hsu. SUMMIT: A simulator for urban driving in massive mixed traffic. In Proc. IEEE Int. Conf. on Robotics & Automation, 2020.
BibTeX PDF

@inproceedings{CaiLee20,
	Author = {P. Cai and Y. Lee and Y. Luo and D. Hsu },
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Autonomous Driving},
	Booktitle = ICRA,
	Title = {{SUMMIT}: A Simulator for Urban Driving in Massive Mixed Traffic},
	Year = {2020}}

Y. Xie, I.P. Bodala, D.C. Ong, D. Hsu, and H. Soh. Robot capability and intention in trust-based decisions across tasks. In Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction, 2019.
BibTeX PDF

@inproceedings{XieBod19,
	Author = {Y. Xie and I.P. Bodala and D.C. Ong and D. Hsu and H. Soh},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Human-Robot Interaction,Trust-Aware Decision Making},
	Booktitle = HRI,
	Title = {Robot Capability and Intention in Trust-based Decisions across Tasks},
	Year = {2019}}

M. Meghjani, Y.F. Luo, Q.H. Ho, P. Cai, S. Verma, D. Rus, and D. Hsu. Context and intention aware planning for urban driving. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2019.
BibTeX PDF

@inproceedings{MegLuo19,
	Author = {M. Meghjani and Y.F. Luo and Q.H. Ho and P. Cai and S. Verma and D. Rus and D. Hsu},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {POMDP Applications, Autonomous Driving},
	Booktitle = IROS,
	Title = {Context and Intention Aware Planning for Urban Driving},
	Year = {2019}}

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

@article{LuoBai19,
	Author = {Luo, Y.F. and Bai, H.Y. and Hsu, D. and Lee, W.S.},
	Bib2Html_Pubtype = {Journal},
	Bib2Html_Rescat = {POMDP Planning},
	Journal = IJRR,
	Number = {2--3},
	Pages = {162--181},
	Title = {Importance Sampling for Online Planning under Uncertainty},
	Volume = {38},
	Year = {2019}}

R. Pinsler, P. Karkus, A. Kupcsik, D. Hsu, and W.S. Lee. Factored contextual policy search with bayesian optimization. In Proc. IEEE Int. Conf. on Robotics & Automation, 2019.
BibTeX PDF

@inproceedings{PinKar19,
	Author = {R. Pinsler and P. Karkus and A. Kupcsik and D. Hsu and W.S. Lee},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Reinforcement Learning},
	Booktitle = ICRA,
	Title = {Factored Contextual Policy Search with Bayesian Optimization},
	Year = {2019}}

N.P. Garg, D. Hsu, and W.S. Lee. Learning to grasp under uncertainty using POMDPs. In Proc. IEEE Int. Conf. on Robotics & Automation, 2019.
BibTeX PDF

@inproceedings{GarHsu19,
	Author = {N.P. Garg and D. Hsu and W.S. Lee},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Deep Learning},
	Booktitle = ICRA,
	Title = {Learning To Grasp Under Uncertainty Using POMDPs},
	Year = {2019}}

P. Karkus, X. Ma, D. Hsu, L.P. Kaelbling, W.S. Lee, and T. Lozano-Perez. Differentiable algorithm networks for composable robot learning. In Proc. Robotics: Science & Systems, 2019.
BibTeX PDF

@inproceedings{KarMa19,
	Author = {P. Karkus and X. Ma and D. Hsu and L.P. Kaelbling and W.S. Lee and T. Lozano-Perez},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Deep Learning},
	Booktitle = RSS,
	Title = {Differentiable Algorithm Networks for Composable Robot Learning},
	Year = {2019}}

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

@inproceedings{GarHsu19a,
	Author = {N.P. Garg and D. Hsu and W.S. Lee},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {POMDP Planning},
	Booktitle = RSS,
	Title = {{DESPOT-$\alpha$}: Online {POMDP} Planning With Large State and Observation Spaces},
	Year = {2019}}

P.P. Cai, Y.F. Luo, A. Saxena, D. Hsu, and W.S. Lee. LeTS-Drive: Driving in a crowd by learning from tree search. In Proc. Robotics: Science & Systems, 2019.
BibTeX PDF

@inproceedings{CaiLuo19,
	Author = {P.P. Cai and Y.F. Luo and A. Saxena and D. Hsu and W.S. Lee},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {POMDP Planning,Deep Learning,Autonomous Driving},
	Booktitle = RSS,
	Title = {{LeTS-Drive}: {Driving} in a Crowd by Learning from Tree Search},
	Year = {2019}}

P. Karkus, D. Hsu, and W.S. Lee. Particle filter networks with application to visual localization. In Proc. Conference on Robot Learning. 2018.
BibTeX PDF

@incollection{KarHsu18,
	Author = {P. Karkus and D. Hsu and W.S. Lee},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Deep Learning, Planning and Learning},
	Booktitle = CORL,
	Editor = {S. Levine and V. Vanhoucke and K. Goldberg},
	Pages = {169--178},
	Series = PMLR,
	Title = {Particle Filter Networks with Application to Visual Localization},
	Volume = {87},
	Year = {2018}}

Y.F. Luo, P. Cai, A. Bera, D. Hsu, W.S. Lee, and D. Manocha. PORCA: Modeling and planning for autonomous driving among many pedestrians. IEEE Robotics & Automation Letters, 3(4):3418–3425, 2018.
BibTeX PDF

@article{LuoCai18,
	Author = {Y.F. Luo and P. Cai and A. Bera and D. Hsu and W.S. Lee and D. Manocha},
	Bib2Html_Pubtype = {Journal},
	Bib2Html_Rescat = {POMDP Applications},
	Journal = RAL,
	Number = {4},
	Pages = {3418--3425},
	Title = {{PORCA}: Modeling and Planning for Autonomous Driving Among Many Pedestrians},
	Volume = {3},
	Year = {2018}}

M. Chen, D. Hsu, and W.S. Lee. Guided exploration of human intentions for human-robot interaction. In Algorithmic Foundations of Robotics XIII—Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2018.
BibTeX PDF

@incollection{CheHsu18,
	Author = {Chen, M. and Hsu, D. and Lee, W.S.},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Planning and Learning under Uncertainty},
	Booktitle = WAFR18,
	Title = {Guided Exploration of Human Intentions for Human-Robot Interaction},
	Year = {2018}}

H. Soh, P. Shu, M. Chen, and D. Hsu. The transfer of human trust in robot capabilities across tasks. In Proc. Robotics: Science & Systems, 2018.
BibTeX PDF

@inproceedings{SohShu18,
        Author = {H. Soh and P. Shu and M. Chen and D. Hsu},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {Human-Robot Interaction},
        Booktitle = {Proc. Robotics: Science \& Systems},
        Title = {The Transfer of Human Trust in Robot Capabilities across Tasks},
        Year = {2018}}

J.K. Li, D. Hsu, and W.S. Lee. Push-Net: Deep planar pushing for objects with unknown physical properties. In Proc. Robotics: Science & Systems, 2018.
BibTeX PDF

@inproceedings{LiHsu18,
        Author = {J.K. Li and D. Hsu and W.S. Lee},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {Deep Learning},
        Booktitle =  {Proc. Robotics: Science \& Systems},
        Title = {Push-Net: Deep Planar Pushing for Objects with Unknown Physical Properties},
        Year = {2018}}

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

@inproceedings{CaiLuo18,
        Author = {P.P. Cai and Y.F. Luo and D. Hsu and W.S. Lee},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {POMDP Planning},
        Booktitle =  {Proc. Robotics: Science \& Systems},
        Title = {HyP-DESPOT: A Hybrid Parallel Algorithm for Online Planning under Uncertainty},
        Year = {2018}}

M. Shridhar and D. Hsu. Interactive visual grounding of referring expressions for human-robot interaction. In Proc. Robotics: Science & Systems, 2018.
BibTeX PDF

@inproceedings{ShrHsu18,
        Author = {M. Shridhar and D. Hsu},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {Human-Robot Interaction},
        Booktitle =  {Proc. Robotics: Science \& Systems},
        Title = {Interactive Visual Grounding of Referring Expressions for Human-Robot Interaction},
        Year = {2018}}

Z. Lan, D. Hsu, and G. Lee. Solving the perspective-2-point problem for flying-camera photo composition. In Proc. IEEE Conf. on Computer Vision & Pattern Recognition, 2018.
BibTeX PDF

@inproceedings{LanHsu18,
        Author = {Z. Lan and D. Hsu and G.H. Lee},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {Human-Robot Interaction},
        Booktitle = {Proc. IEEE Conf. on Computer Vision \& Pattern Recognition},
        Title = {Solving the Perspective-2-Point Problem for Flying-Camera Photo Composition},
        Year = {2018}}

M. Chen, S. Nikolaidis, H. Soh, D. Hsu, and S. Srinivasa. Planning with trust for human-robot collaboration. In Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction, 2018.
BibTeX PDF

@inproceedings{CheNik18,
        Author = {M. Chen and S. Nikolaidis and H. Soh and D. Hsu and S. Srinivasa},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {Human-Robot Interaction},
        Booktitle = {Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction},
        Title = {Planning with Trust for Human-Robot Collaboration},
        Year = {2018}}

P. Karkus, D. Hsu, and W. Lee. QMDP-Net: Deep learning for planning under partial observability. In Advances in Neural Information Processing Systems, 2017.
BibTeX PDF

@inproceedings{KarHsu17,
        Author = {P. Karkus and D. Hsu and W.S. Lee},
        Bib2Html_Pubtype = {Refereed Conference and Workshop},
        Bib2Html_Rescat = {Deep Learning, Planning and Learning},
        Booktitle = {Advances in Neural Information Processing Systems},
        Title = {QMDP-Net: Deep Learning for Planning under Partial Observability},
        Year = {2017}}

W. Gao, D. Hsu, W. Lee, S. Shen, and K. Subramanian. Intention-Net: Integrating planning and deep learning for goal-directed autonomous navigation. In S. Levine and V. V. and K. Goldberg, editors, Conference on Robot Learning, volume 78 of Proc. Machine Learning Research, pages 185–194. 2017.
BibTeX PDF

@incollection{GaoHsu17,
	Author = {W. Gao and D. Hsu and W.S. Lee and S. Shen and K. Subramanian},
	Bib2Html_Pubtype = {Refereed Conference and Workshop},
	Bib2Html_Rescat = {Deep Learning, Planning and Learning},
	Booktitle = {Conference on Robot Learning},
	Editor = {S. Levine and V. Vanhoucke andK. Goldberg},
	Pages = {185-194},
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	Title = {Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation},
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S. Nikolaidis, D. Hsu, and S. Srinivasa. Human-robot mutual adaptation in collaborative tasks: Models and experiments. Int. J. Robotics Research, 36(5–7):618–634, 2017.
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S. Nikolaidis, Y. Zhu, D. Hsu, and S. Srinivasa. Human-robot mutual adaptation in shared autonomy. In Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction, 2017.
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N. Ye, A. Somani, D. Hsu, and W. Lee. DESPOT: Online POMDP planning with regularization. J. Artificial Intelligence Research, 58:231–266, 2017.
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P. Singh, M. Chen, L. Carlone, S. Karaman, E. Frazzoli, and D. Hsu. Supermodular mean squared error minimization for sensor scheduling in optimal kalman filtering. In Proc. American Control Conf., 2017.
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Z. Lim, D. Hsu, and W. Lee. Shortest path under uncertainty: Exploration versus exploitation. In Proc. Conf. on Uncertainty in Artificial Intelligence, 2017.
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Z. Lan, M. Shridhar, D. Hsu, and S. Zhao. XPose: Reinventing user interaction with flying cameras. In Proc. Robotics: Science & Systems, 2017.
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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.
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M. Koval, D. Hsu, N. Pollard, and S. Srinivasa. Configuration lattices for planar contact manipulation under uncertainty. In Algorithmic Foundations of Robotics XII – Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2016.
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S. Nikolaidis, A. Kuznetsov, D. Hsu, and S. Srinivasa. Formalizing human-robot mutual adaptation: A bounded memory model. In Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction. 2016.
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Z.W. Lim, D. Hsu, and W.S. Lee. Adaptive informative path planning in metric spaces. Int. J. Robotics Research, 35(5):585-598, 2016.
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J.K. Li, D. Hsu, and W.S. Lee. Act to see and see to act: POMDP planning for objects search in clutter. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2016.
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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.
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H.Y. Bai, S.J. Cai, N. Ye, D. Hsu, and W.S. Lee. Intention-aware online POMDP planning for autonomous driving in a crowd. In Proc. IEEE Int. Conf. on Robotics & Automation, 2015.
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V. Sezer, T. Bandyopadhyay, D. Rus, E. Frazzoli, and D. Hsu. Towards autonomous navigation of unsignalized intersections under uncertainty of human driver intent. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2015.
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Z.W. Lim, D. Hsu, and W.S. Lee. Adaptive stochastic optimization: from sets to paths. In Advances in Neural Information Processing Systems, 2015.
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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.
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A. Kupcsik, D. Hsu, and W.S. Lee. Learning dynamic robot-to-human object handover from human feedback. In Proc. Int. Symp. on Robotics Research, 2015.
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K. Wu, W.S. Lee, and D. Hsu. POMDP to the rescue: Boosting performance for Robocup rescue. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2015.
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G.M. Gyori, G. Venkatachalam, P.S. Thiagarajan, D. Hsu, and M.V. Clement. OpenComet: An automated tool for comet assay image analysis. Redox Biology, 2(2):457–465, 2014.
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X.X. Wang, Y. Wang, D. Hsu, and Y. Wang. Exploration in interactive personalized music recommendation: A reinforcement learning approach. ACM Trans. on Multimedia Computing, Communications & Applications, 11(1), 2014.
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Z.W. Lim, D. Hsu, and W.S. Lee. Adaptive informative path planning in metric spaces. In Algorithmic Foundations of Robotics XI—Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2014.
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Z. Zhang, D. Hsu, and L.S. Lee. Covering number for efficient heuristic-based POMDP planning. In Proc. Int. Conf. on Machine Learning. 2014.
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H.Y. Bai, D. Hsu, and W.S. Lee. Integrated perception and planning in the continuous space: A POMDP approach. Int. J. Robotics Research, 33(9):1288–1302, 2014.
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S.K. Palaniappan, B.M. Gyori, B. Liu, D. Hsu, and P.S. Thiagarajan. Statistical model checking based calibration and analysis of bio-pathway models. In Proc. Conf. on Computational Methods in Systems Biology, 2013.
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H.Y. Bai, D. Hsu, and W.S. Lee. Planning how to learn. In Proc. IEEE Int. Conf. on Robotics & Automation, 2013.
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P. Chaudhari, S. Karaman, D. Hsu, and E. Frazzoli. Sampling-based algorithms for continuous-time POMDPs. In Proc. American Control Conf., 2013.
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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.
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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.
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B. Gipson, D. Hsu, L.E. Kavraki, and J.C. Latombe. Computational models of protein kinematics and dynamics: Beyond simulation. Annu. Rev. Anal. Chem, 5:273–291, 2012. DOI: 10.1146/annurev-anchem-062011-143024.
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Y. Wang, K.S. Won, D. Hsu, and W.S. Lee. Monte Carlo Bayesian reinforcement learning. In Proc. Int. Conf. on Machine Learning, 2012.
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T. Bandyopadhyay, K.S. Won, E. Frazzoli, D. Hsu, W.S. Lee, and D. Rus. Intention-aware motion planning. In Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2012.
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B. Liu, J. Zhang, P.Y. Tan, D. Hsu, A.M. Blom, B. Leong, S. Sethi, B. Ho, J.L. Ding, and P.S. Thiagarajan. A computational and experimental study of the regulatory mechanisms of the complement system. PloS Computational Biology, 7(1), 2011.
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B. Liu, D. Hsu, and P. S. Thiagarajan. Probabilistic approximations of ODEs-based bio-pathway dynamics. Theoretical Computer Science, 412(21):2188-2206, 2011.
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G. Koh, D. Hsu, and P. S. Thiagarajan. Component-based construction of bio-pathway models: The parameter estimation problem. Theoretical Computer Science, 412(26):2840–2853, 2011.
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H.Y. Bai and D. Hsu and Mykel J. Kochenderfer and W.S. Lee. Unmanned aircraft collision avoidance using continuous-state POMDPs. In Proc. Robotics: Science and Systems, 2011.
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T.H.D. Nguyen and D. Hsu and W.S. Lee and T.Y. Leong and L.P. Kaelbling and T. Lozano-Perez and A.H. Grant. CAPIR: Collaborative action planning with intention recognition. Proc. AI and Interactive Digital Entertainment Conference, 2011.
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H. Kurniawati and Y. Du and D. Hsu and W.S. Lee. Motion planning under uncertainty for robotic tasks with long time horizons. Int. J. Robotics Research, 30(3):308-323, 2011.
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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.
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G. Koh, D. Hsu, and P.S. Thiagarajan. Incremental signaling pathway modeling by data integration. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), 2010.
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T.-H. Chiang, D. Hsu, and J.C. Latombe. Markov dynamic models for long-timescale protein motion. Bioinformatics, 26(12):i269–i277, 2010. Special issue on Int. Conf. on Intelligent Systems for Molecular Biology (ISMB) 2010.
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Y.Z. Du, D. Hsu, H. Kurniawati, W.S. Lee, S.C.W. Ong, and S.W. Png. A POMDP Approach to Robot Motion Planning under Uncertainty. In Int. Conf. on Automated Planning & Scheduling, Workshop on Solving Real-World POMDP Problems, 2010.
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L.L. Ko, D. Hsu, W.S. Lee, and S.C.W. Ong. Structured parameter elicitation. In Proc. AAAI Conf. on Artificial Intelligence, 2010.
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S.C.W. Ong, S.W. Png, D. Hsu, and W.S. Lee. Planning under Uncertainty for Robotic Tasks with Mixed Observability. Int. J. Robotics Research, 29(8):1053–1068, 2010.
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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.
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B. Liu, P.S. Thiagarajan, and D. Hsu . Probabilistic approximations of signaling pathway dynamics. In Proc. Conf. on Computational Methods in Systems Biology, 2009.
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B. Liu, P.S. Thiagarajan, and D. Hsu. Probabilistic approximations of bio-pathway dynamics. In ACM Int. Conf. on Computational Biology (RECOMB) Poster Book, 2009.
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S.C.W. Ong, D. Hsu, W.S. Lee, and H. Kurniawati. Partially observable Markov decision process POMDP technologies for sign language based human-computer interaction. In Proc. Int. Conf. on Human-Computer Interaction, 2009.
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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.
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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.
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T. Bandyopadhyay, N. Rong, Ang Jr., M.H., D. Hsu, and W.S. Lee. Motion planning for people tracking in uncertain and dynamic environments. In IEEE Int. Conf. on Robotics & Automation, Workshop on People Detection & Tracking, 2009.
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G. Koh, D. Hsu, and P.S. Thiagarajan. Composition of signaling pathway models and its application to parameter estimation. In ACM Int. Conf. on Computational Biology (RECOMB) Poster Book, 2008.
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A. Nigham, L. Tucker-Kellogg, I. Mihalek, C. Verma, and D. Hsu. pFlexAna: Detecting conformational changes in remotely related proteins. Nucleic Acids Res., 36:W246–W251, 2008. DOI: 10.1093/nar/gkn259.
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A. Nigham and D. Hsu. Protein conformational flexibility analysis with noisy data. J. Computational Biology, 15(7):813–828, 2008.
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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.
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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.
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D. Hsu, W.S. Lee, and N. Rong. A point-based POMDP planner for target tracking. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2644–2650, 2008.
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T. Bandyopadhyay, D. Hsu, and Ang Jr., M.H.. Motion strategies for people tracking in cluttered dynamic environments. In Proc. Int. Symp. on Experimental Robotics, 2008.
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L.J. Guibas, D. Hsu, H. Kurniawati, and E. Rehman. Bounded uncertainty roadmaps for path planning. In Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2008.
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G. Koh, L. Tucker-Kellogg, D. Hsu, and P.S. Thiagarajan. Globally consistent pathway parameter estimates through belief propagation. In Proc. Workshop on Algorithms in Bioinformatics (WABI), 2007.
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A. Nigham and D. Hsu. Protein conformational flexibility analysis with noisy data. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pp. 396–411, 2007.
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T.-H. Chiang, M.S. Apaydin, D.L. Brutlag, D. Hsu, and J.C. Latombe. Using stochastic roadmap simulation to predict experimental quantities in protein folding kinetics: Folding rates and phi-values. J. Computational Biology, 14(5):578–593, 2007.
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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.
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T. Bandyopadhyay, Ang Jr., M.H., and D. Hsu. Motion planning for 3-D target tracking among obstacles. In Proc. Int. Symp. on Robotics Research, 2007.
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X. Wu, D. Hsu, and A.K.H. Tung. Efficient constrained Delaunay triangulation for large spatial databases. Technical Report TRA1/06, National University of Singapore, School of Computing, 2006.
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G. Koh, H.F.C. Teong, M.-V. Clément, D. Hsu, and P.S. Thiagarajan. A decompositional approach to parameter estimation in pathway modeling: A case study of the Akt and MAPK pathways and their crosstalk. Bioinformatics, 22(14):271–280, 2006. Special issue on Int. Conf. on Intelligent Systems for Molecular Biology (ISMB) 2006.
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T.-H. Chiang, M.S. Apaydin, D.L. Brutlag, D. Hsu, and J.C. Latombe. Predicting experimental quantities in protein folding kinetics using stochastic roadmap simulation. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pp. 410–424, Springer, 2006.
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T. Bandyopadhyay, Y.P. Li, Ang Jr., M.H., and D. Hsu. A greedy strategy for tracking a locally predictable target among obstacles. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2342–2347, 2006.
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H. Kurniawati and D. Hsu. Workspace-based connectivity oracle: An adaptive sampling strategy for PRM planning. In S. Akella and others, editors, Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), Springer, 2006.
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H.-L. Cheng, D. Hsu, J.-C. Latombe, and G. Sánchez-Ante. Multi-level free-space dilation for sampling narrow passages in PRM planning. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 1255–1260, 2006.
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D. Hsu, J.C. Latombe, and H. Kurniawati. On the probabilistic foundations of probabilistic roadmap planning. Int. J. Robotics Research, 25(7):627–643, 2006.
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H.H. González-Baños, D. Hsu, and J.C. Latombe. Motion planning: Recent developments. In S.S. Ge and F.L. Lewis, editors, Autonomous Mobile Robots: Sensing, Control, Decision-Making and Applications, CRC Press, 2006.
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J. Yin, Y. Wang, and D. Hsu. Digital violin tutor: An integrated system for beginning violin learners. In Proc. ACM Multimedia, pp. 976–985, 2005.
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Z. Sun, D. Hsu, T. Jiang, H. Kurniawati, and J. Reif. Narrow passage sampling for probabilistic roadmap planners. IEEE Trans. on Robotics, 21(6):1105–1115, 2005.
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D. Hsu, G. Sánchez-Ante, and Z. Sun. Hybrid PRM sampling with a cost-sensitive adaptive strategy. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 3885–3891, 2005.
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D. Hsu, J.C. Latombe, and H. Kurniawati. On the probabilistic foundations of probabilistic roadmap planning. In Proc. Int. Symp. on Robotics Research, 2005.
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M. Erdmann, D. Hsu, M. Overmars, and F. van der Stappen, editors. Algorithmic Foundations of Robotics VI, Springer, 2005.
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C. Xia, D. Hsu, and A.K.H. Tung. A fast filter for obstructed nearest neighbour queries. In Proc. British National Conferences on Databases, 2004.
BibTeX

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T. Bandyopadhyay, Y.P. Li, Ang Jr., M.H., and D. Hsu. Stealth tracking of an unpredictable target among obstacles. In M. Erdmann and others, editors, Algorithmic Foundations of Robotics VI—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 43–58, Springer, 2004.
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J. Yin, A. Dhanik, D. Hsu, and Y. Wang. The creation of a music-driven digital violinist. In Proc. ACM Multimedia, pp. 476–479, 2004.
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H. Kurniawati and D. Hsu. Workspace importance sampling for probabilistic roadmap planning. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, pp. 1618–1623, 2004.
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D. Hsu and Z. Sun. Adaptive hybrid sampling for probabilistic roadmap planning. Technical Report TRA5/04, National University of Singapore, School of Computing, 2004.
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D. Hsu and Z. Sun. Adaptively combining multiple sampling strategies for probabilistic roadmap planning. In Proc. IEEE Conf. on Robotics, Automation, and Mechatronics, pp. 774–779, 2004.
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M.S. Apaydin, D.L. Brutlag, C. Guestrin, D. Hsu, J.C. Latombe, and C. Varma. Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion. J. Computational Biology, 10(3-4):247–281, 2003.
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D. Hsu, T. Jiang, J. Reif, and Z. Sun. The bridge test for sampling narrow passages with probabilistic roadmap planners. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 4420–4426, 2003.
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D. Brutlag, M.S. Apaydin, C. Guestrin, D. Hsu, C. Varma, A. Singh, and J.-C. Latombe. Using robotics to fold proteins and dock ligands. Bioinformatics, 18:S74–S83, 2002.
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R.-P. Berretty, D. Hsu, L. Kettner, A. Mascarenhas, M.R. Redinbo, and J. Snoeyink. Ligand binding to the pregnane X receptor by geometric matching of hydrogen bonding. In L. Florea and others, editors, Currents in Computational Molecular Biology, pp. 22–23, 2002. The booklet contains extended poster abstracts from RECOMB 2002.
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M.S. Apaydin, D.L. Brutlag, C. Guestrin, D. Hsu, and J.C. Latombe. Stochastic conformational roadmaps for computing ensemble properties of molecular motion. In J.-D. Boissonnat and others, editors, Algorithmic Foundations of Robotics V—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 131–148, Springer, 2002.
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M.S. Apaydin, D.L. Brutlag, C. Guestrin, D. Hsu, and J.C. Latombe. Stochastic roadmap simulation: An efficient representation and algorithm for analyzing molecular motion. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pp. 12–21, 2002.
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D. Hsu, R. Kindel, J.C. Latombe, and S. Rock. Randomized kinodynamic motion planning with moving obstacles. Int. J. Robotics Research, 21(3):233–255, 2002.
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J. Basch, L.J. Guibas, D. Hsu, and A.T. Nguyen. Disconnection proofs for motion planning. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 1765–1772, 2001.
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L.J. Guibas, D. Hsu, and L. Zhang. A hierarchical method for real-time distance computation among moving convex bodies. Computational Geometry: Theory and Applications, 15(1-3):51–68, 2000.
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R. Kindel, D. Hsu, J.C. Latombe, and S. Rock. Kinodynamic motion planning amidst moving obstacles. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 537–543, 2000.
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D. Hsu, R. Kindel, J.C. Latombe, and S. Rock. Control-based randomized motion planning for dynamic environments. In B.R. Donald and others, editors, Algorithmic and Computational Robotics: New Directions—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 247–264, A. K. Peters, Wellesley, MA, 2000.
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D. Hsu. Randomized Single-query Motion Planning in Expansive Spaces. Ph.D. Thesis, Dept. of Computer Science, Stanford University, Stanford, CA, 2000.
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L.J. Guibas, D. Hsu, and L. Zhang. H-Walk: hierarchical distance computation for moving convex bodies. In Proc. ACM Symp. on Computational Geometry, pp. 265–273, 1999.
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D. Hsu, J.C. Latombe, and S. Sorkin. Placing a robot manipulator amid obstacles for optimized execution. In Proc. IEEE Int. Symp. on Assembly & Task Planning, pp. 280–285, 1999.
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D. Hsu, J.C. Latombe, and R. Motwani. Path planning in expansive configuration spaces. Int. J. Computational Geometry & Applications, 9(4-5):495–512, 1999.
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D. Hsu, J.C. Latombe, R. Motwani, and L.E. Kavraki. Capturing the connectivity of high-dimensional geometric spaces by parallelizable random sampling techniques. In P.M. Pardalos and S. Rajasekaran, editors, Advances in randomized parallel computing, pp. 159–182, Kluwer Academic Publishers, Boston, MA, 1999.
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D. Hsu, L.E. Kavraki, J.C. Latombe, R. Motwani, and S. Sorkin. On finding narrow passages with probabilistic roadmap planners. In P.K. Agarwal and others, editors, Robotics: The Algorithmic Perspective—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 141–154, A. K. Peters, Wellesley, MA, 1998.
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D. Hsu, J.C. Latombe, and R. Motwani. Path planning in expansive configuration spaces. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2719–2726, 1997.
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H. Alt, D. Hsu, and J. Snoeyink. Computing the largest inscribed isothetic rectangle. In Proc. Canadian Conf. on Computational Geometry, pp. 67–72, 1995.
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