Publications

You can also see my Google scholar profile.

2022

  • J.-S. Ha, D. Driess, and M. Toussaint, “Deep Visual Constraints: Neural Implicit Models for Manipulation Planning from Visual Input,” Preprint. [PDF] [Video] [Project Page]

2021

  • D. Driess, J.-S. Ha, and M. Toussaint, “Learning to Solve Sequential Physical Reasoning Problems from a Scene Image,” The International Journal of Robotics Research (IJRR), 2021, 40.12-14: 1435-1466. [Link]

  • D. Driess, J.-S. Ha, R. Tedrake, and M. Toussaint, “Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning,” Conference on Robot Learning (CoRL), Nov. 2021. [PDF] [Video]

  • J. Ortiz-Haro, J.-S. Ha, D. Driess, and M. Toussaint, “Structured deep generative models for sampling on constraint manifolds in sequential manipulation,” Conference on Robot Learning (CoRL), Nov. 2021. [PDF]

  • M. Toussaint, J.-S. Ha, and O. Oguz, “Co-Optimizing Robot, Environment, and Tool Design via Joint Manipulation Planning,” IEEE International Conference on Robotics and Automation (ICRA), May 2021. [PDF] [Video]

  • D. Driess*, J.-S. Ha*, R. Tedrake, and M. Toussaint, “Learning Geometric Reasoning and Control for Long-Horizon Tasks from Visual Input,” IEEE International Conference on Robotics and Automation (ICRA), May 2021. [PDF] [Video] *equal contribution

  • J.-S. Ha*, Y.-J. Park*, H.-J. Chae, S.-S. Park, and H.-L. Choi, “Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning,” IEEE International Conference on Robotics and Automation (ICRA), May 2021. [PDF] [Video] *equal contribution

  • J.-S. Ha, H.-J. Chae, and H.-L. Choi, “A diffusion wavelets-based multiscale framework for inverse optimal control of stochastic systems,” International Journal of Systems Science, 2021. [PDF]

2020

  • M. Toussaint, J.-S. Ha, and D. Driess, “Describing Physics For Physical Reasoning: Force-based Sequential Manipulation Planning,” IEEE Robotics and Automation Letters (RA-L/IROS 20), 2020, 5.4: 6209 - 6216. [PDF] [Video]

  • D. Driess, J.-S. Ha, and M. Toussaint, “Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image,” Robotics: Science and Systems (R:SS), July 2020. [PDF] [Video]

  • J.-S. Ha, D. Driess, and M. Toussaint, “A Probabilistic Framework for Constrained Manipulations and Task and Motion Planning under Uncertainty,” IEEE International Conference on Robotics and Automation (ICRA), May 2020. [PDF] [Video]

  • D. Driess, O. Oguz, J.-S. Ha, and M. Toussaint, “Deep Visual Heuristics: Learning Feasibility of Mixed-Integer Programs for Manipulation Planning,” IEEE International Conference on Robotics and Automation (ICRA), May 2020. Nominated for Best Paper Award in Automation [PDF] [Video]

2019

  • J.-S. Ha, Y.-J. Park, H.-J. Chae, S.-S. Park, and H.-L. Choi, “Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems,” Journal of Statistical Mechanics: Theory and Experiment, 2019: 124008. [PDF] [arXiv]

  • S.-S. Park, Y. Min, J.-S. Ha, D.-H. Cho, and H.-L. Choi, “A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking,” IEEE Access, 2019, 7: 163589-163603. [PDF]

  • J.-S. Ha, S.-S. Park, and H.-L. Choi, “A Topology-Guided Path Integral Approach for Stochastic Optimal Control in Cluttered Environment,” Robotics and Autonomous Systems, 2019, 113: 81-93. [PDF] [arXiv]

  • J.-S. Ha, and H.-L. Choi, “On Periodic Optimal Solutions of Persistent Sensor Planning for Continuous-Time Linear Systems,” Automatica, 2019, 99: 138-148. [PDF]

2018

  • J.-S. Ha, Y.-J. Park, H.-J. Chae, S.-S. Park, and H.-L. Choi, “Adaptive Path-Integral Autoencoder: Representation Learning and Planning for Dynamical Systems,” Neural Information Processing Systems (NeurIPS), Dec. 2018. [PDF] [Video]

  • J.-S. Ha, H.-J. Chae, and H.-L. Choi, “Approximate Inference-based Motion Planning by Learning and Exploiting Low-Dimensional Latent Variable Models,” IEEE Robotics and Automation Letters (RA-L/IROS’18), 2018, 3.4: 3892-3899. [PDF] [Video]

  • J.-S. Ha, H.-J. Chae, and H.-L. Choi, “A Stochastic Game-Based Approach for Cooperative Beyond-Visual-Range Air Combat,” Unmanned Systems, 2018, 6(01): 67-79. [PDF]

  • J.-S. Ha, and H.-L. Choi, J. Jeon, “Iterative Methods for Efficient Sampling-Based Optimal Motion Planning of Nonlinear Systems,” International Journal of Applied Mathematics & Computer Science, 2018, 28(1): 155-168. [PDF]

  • J.-S. Ha, Y.-J. Park, H.-J. Chae, S.-S. Park, and H.-L. Choi, “High-dimensional Motion Planning and Control using Low-dimensional Latent Variable Models,” RSS Pioneers, June 2018.

  • J.-S. Ha, Y.-J. Park, H.-J. Chae, S.-S. Park, and H.-L. Choi, “Adaptive Path-Integral Approach for Representation Learning and Planning,” International Conference on Learning Representations (ICLR) Workshop, April 2018. [PDF]

2017

  • J.-S. Ha, and H.-L. Choi, “Multiscale Abstraction, Planning and Control using Diffusion Wavelets for Stochastic Optimal Control Problems,” IEEE International Conference on Robotics and Automation (ICRA), May 2017. [PDF]

  • J. Kim, J.-S. Ha, and H.-L. Choi, “A Quadratic-Cost Dual Control Approach for Trajectory Optimization,” International Journal of Control, Automation and Systems, 2017, 15(5): 2253-2261. [PDF]

2016

  • D.-H. Cho, J.-S. Ha, S.-J. Lee, S.-H. Moon, and H.-L. Choi, “Informative Path Planning and Mapping with Multiple UAVs in Wind Fields,” International Symposium on Distributed Autonomous Robotic Systems (DARS), Nov. 2016. [PDF]

  • J.-S. Ha, and H.-L. Choi, “A Topology-Guided Path Integral Approach for Stochastic Optimal Control,” IEEE International Conference on Robotics and Automation (ICRA), May 2016. [PDF]

  • J.-S. Ha, and H.-L. Choi, “Multiscale Inverse Reinforcement Learning using Diffusion Wavelets,” NIPS Workshop on Interpretable Machine Learning, Dec. 2016. [PDF]

  • J.-S. Ha, and H.-L. Choi, “Stochastic Optimal Control in Cluttered Environment with Topological Motion Planning,” Korean Society for Industrial and Applied Mathematics (KSIAM), May 2016.

  • J.-S. Ha, and H.-L. Choi, “Asymptotically Optimal Sampling-Based Topological Motion Planning Algorithms and its Application to Stochastic Optimal Control,” ICRA Workshop on Emerging Topological Techniques in Robotics, May 2016.

2015

  • J.-S. Ha, H.-J. Chae, and H.-L. Choi, “A Stochastic Game-Theoretic Approach for Analysis of Multiple Cooperative Air Combat,” American Control Conference (ACC), July 2015. [PDF]

  • H.-L. Choi, and J.-S. Ha, “Informative Windowed Forecasting of Continuous-time Linear Systems for Mutual Information-based Sensor Planning,” Automatica, 2015, 57: 97-104. [PDF]

2014

  • J.-S. Ha, and H.-L. Choi, “Periodic Sensing Trajectory Generation for Persistent Monitoring,” IEEE Conference on Decision and Control (CDC), Dec. 2014. [PDF]

  • B.-M. Jeong, J.-S. Ha, and H.-L. Choi, “MDP-based Mission Planning for Multi-UAV Persistent Surveillance”, International Conference on Control, Automation and Systems (ICCAS), Oct. 2014. [PDF]

2013

  • J.-S. Ha, J.-J. Lee, and H.-L. Choi, “A Successive Approximation-Based Approach for Optimal Kinodynamic Motion Planning with Nonlinear Differential Constraints,” IEEE Conference on Decision and Control (CDC), Dec. 2013. [PDF]

2012

  • J.-S. Ha, and J.-J. Lee, “Position Control of Mobile Two Wheeled Inverted Pendulum Robot by Sliding Mode Control,” International Conference on Control, Automation and Systems (ICCAS), Oct. 2012. [PDF]

  • J.-W. Lee, J.-H. Seok, J.-S. Ha, J.-J. Lee, and H.-J. Lee, “Temporal Waypoint Revision Method to Solve Path Mismatch Problem of Hierarchical Integrated Path Planning for Mobile Vehicle,” Journal of Institute of Control, Robotics and Systems, 2012, 18(7): 664-668. [PDF]