Multi-Agent Robotic Systems Lab

Publications

Journal Papers

  • Seth Siriya, Mo Chen, Ye Pu, “Real-Time Safety-Guaranteed Trajectory Planning and Tracking for Time-Varying Systems,” IEEE Transactions on Automatic Control, to appear.
  • Chong He*, Zheng Gong*, Mo Chen, and Sylvia L. Herbert, “Efficient and Guaranteed Hamilton-Jacobi Reachability via Self-Contained Subsystem Decomposition and Admissible Control Sets,” IEEE Control Systems Letters, vol. 7, pp. 3824-3829, Dec. 2023 [paper]
  • Pedram Agand, Allison Kennedy, Trevor Harris, Chanwoo Bae, Mo Chen, and Edward J. Park, “Fuel Consumption Prediction for a Passenger Ferry using Machine Learning and In-service Data: A Comparative Study,” Ocean Engineering, 2023 [paper]
  • Juan Chacon, Mo Chen, and Razvan C. Fetecau, “Safe Coverage of Moving Domains for Vehicles with Second Order Dynamics,” IEEE Transactions on Automatic Control, vol. 68, no. 1, pp. 486 – 493, Jan. 2023 [paper]
  • Mohammad Mahdavian, Kangkang Yin, and Mo Chen, “Robust Visual Teach and Repeat for UGVs Using 3D Semantic Maps,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 8590 – 8597, Oct. 2022 [paper | video]
  • Salar Asayesh, Mo Chen, Mehran Mehrandezh, and Kamal Gupta, “Toward Observation Based Least Restrictive Collision Avoidance Using Deep Meta Reinforcement Learning,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 7445–7452, Oct. 2021 [paper]
  • Jimin Rhim, Ji-Hyun Lee, Mo Chen, and Angelica Lim, “A Deeper Look at Autonomous Vehicle Ethics: An Integrative Ethical Decision-Making Framework to Explain Moral Pluralism,” Frontiers in Robotics and AI, vol. 8, May 2021 [paper]
  • Mo Chen, Sylvia L. Herbert, Haimin Hu, Ye Pu, Jaime F. Fisac, Somil Bansal, SooJean Han, and Claire J. Tomlin, “FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking,”IEEE Transactions on Automatic Control, vol. 66, pp. 5861–5876, Dec. 2021 [paper]
  • Zhitian Zhang, Jimin Rhim, Mahdi TaherAhmadi, Kefan Yang, Angelica Lim, and Mo Chen, “SFU-store-nav: A multimodal dataset for indoor human navigation,” Data in Brief, vol. 33, p. 106539, Dec. 2020 [paper]
  • Somil Bansal, Mo Chen, Ken Tanabe, and Claire J. Tomlin, “Provably Safe and Scalable Multivehicle Trajectory Planning,” IEEE Transactions on Control Systems Technology, vol. 29, pp. 2473–2489,Nov. 2020 [paper]
  • Karen Leung, Edward Schmerling, Mengxuan Zhang, Mo Chen, John Talbot, Christian J. Gerdes, Marco Pavone, “On infusing reachability-based safety assurance within planning frameworks for human–robot vehicle interactions,” The International Journal of Robotics Research, vol. 39, no. 10-11, pp. 1326–1345, Sep. 2020 [paper]
  • Mo Chen, Somil Bansal, Jaime F. Fisac, and Claire J. Tomlin, “Robust Sequential Trajectory Planning Under Disturbances and Adversarial Intruder,” IEEE Transactions on Control Systems Technology, vol. 27,no. 4, pp. 1566–1582, Jul. 2019 [paper]
  • Sandeep P. Chinchali, Scott C. Livingston, Mo Chen, and Marco Pavone, “Multi-objective optimal control for proactive decision making with temporal logic models,” The International Journal of Robotics Research, vol. 38, no. 12-13, pp. 1490–1512, Oct. 2019 [paper]
  • Anayo K. Akametalu, Claire J. Tomlin, and Mo Chen, “Reachability-Based Forced Landing System,”Journal of Guidance, Control, and Dynamics, vol. 41, no. 12, pp. 2529–2542, Dec. 2018 [paper]
  • Mo Chen, Sylvia L. Herbert, Mahesh S. Vashishtha, Somil Bansal, and Claire J. Tomlin, “Decomposition of Reachable Sets and Tubes for a Class of Nonlinear Systems,” IEEE Transactions on Automatic Control, vol. 63, no. 11, pp. 3675–3688, Nov. 2018 [paper]
  • Mo Chen and Claire J. Tomlin, “Hamilton–Jacobi Reachability: Some Recent Theoretical Advances and Applications in Unmanned Airspace Management,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 1, no. 1, pp. 333–358, May 2018 [paper]
  • Mo Chen, Qie Hu, Jaime F. Fisac, Anayo K. Akametalu, Casey Mackin, and Claire J. Tomlin, “Reachability-Based Safety and Goal Satisfaction of Unmanned Aerial Platoons on Air Highways,” Journal of Guidance, Control, and Dynamics, vol. 40, no. 6, pp. 1360–1373, Jun. 2017
  • Mo Chen, Zhengyuan Zhou, and Claire J. Tomlin, “Multiplayer Reach-Avoid Games via Pairwise Outcomes,”IEEE Transactions on Automatic Control, vol. 62, no. 3, pp. 1451–1457, Mar. 2017
  • Suraj Gowda, Simon A. Overduin, Mo Chen, Young Hwan Chang, Claire J. Tomlin, and Jose M. Carmena, “Accelerating Submovement Decomposition With Search-Space Reduction Heuristics,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 10, pp. 2508–2515, Oct. 2015
  • Ian M. Mitchell, Shahab Kaynama, Mo Chen, and Meeko Oishi, “Safety preserving control synthesis for sampled data systems,” Nonlinear Analysis: Hybrid Systems, vol. 10, no. 1, pp. 63–82, Nov. 2013 [paper]
  • Mo Chen, Andrzej Kotlicki, Chris Waltham, Nathan Wolfe, Jing Fei Yu, and Chenchong Zhu, “Vibrational behavior of a soundbox in an atmosphere with a variable speed of sound,” The Journal of the Acoustical Society of America, vol. 131, no. 3, pp. 2495–2499, Mar. 2012 [paper]
  • Chris Waltham, Mo Chen, Andrzej Kotlicki, Nathan Wolfe, Jing Fei Yu, and Chenchong Zhu, “Soundbox behavior in environments with varying sound speed.” The Journal of the Acoustical Society of America, vol. 129,no. 4, pp. 2520–2520, Apr. 2011

Conference Papers

  • Tara Toufighi, Minh Bui, Rakesh Shrestha, Mo Chen, “Decision Boundary Learning For Safe Vision-based Navigation via Hamilton-Jacobi Reachability Analysis and Support Vector Machine,” Learning for Dynamics & Control Conference, 2024.
  • Hanyang Hu*, Minh Bui*, and Mo Chen, “Multi-Agent Reach-Avoid Games: Two Attackers Versus One Defender and Mixed Integer Programming,” in Conference on Decision and Control, 2023 [paper]
  • Xubo Lyu, Hanyang Hu, Seth Siriya, Ye Pu, and Mo Chen, “Task-Oriented Koopman-Based Control with Contrastive Encoder,” in Conference on Robot Learning, 2023 (with oral presentation) [paper]
  • Xubo Lyu, Amin Banitalebi-Dehkordi, Mo Chen, and Yong Zhang, “Asynchronous, Option-Based Multi-Agent Policy Gradient: A Conditional Reasoning Approach,” in International Conference on Intelligent Robots and Systems, 2023 [paper]
  • Xinyu Zhao, Razvan C. Fetecau, and Mo Chen, “Efficient Domain Coverage for Vehicles with Second-Order Dynamics via Multi-Agent Reinforcement Learning ,” in International Conference on Intelligent Robots and Systems, 2023 [paper]
  • Sahar Leisiazar, Edward J. Park, Angelica Lim, and Mo Chen, “An MCTS-DRL Based Obstacle and Occlusion Avoidance Methodology in Robotic Follow-Ahead Applications,” in International Conference on Intelligent Robots and Systems, 2023 [paper | slides | project page | video]
  • Pedram Agand, Alex Iskrov, and Mo Chen, “Deep Reinforcement Learning-based Intelligent Traffic Signal Controls with Optimized CO2 emissions,” in International Conference on Intelligent Robots and Systems, 2023 [paper]
  • Pedram Agand, Mo Chen, and Hamid D. Taghirad, “Online Probabilistic Model Identification Using Adaptive Recursive MCMC,” in International Joint Conference on Neural Networks, 2023 [paper]
  • Mohammad Mahdavian*, Payam Nikdel*, Mahdi Taherahmadi, and Mo Chen, “STPOTR: Simultaneous human trajectory and pose prediction using a non-autoregressive transformer for robot follow-ahead,” in International Conference on Robotics and Automation, 2023 [paper | video]
  • Payam Nikdel, Mohammad Mahdavian, and Mo Chen, “DMMGAN: Diverse multi motion prediction of 3D human joints using attention-based generative adversarial network,” in International Conference on Robotics and Automation, 2023 [paper | video]
  • Salar Asayesh, Mo Chen, Mehran Mehrandezh, and Kamal Gupta, “Least-restrictive multi-agent collision avoidance via deep meta reinforcement learning and optimal control,” in International Conference on Robot Intelligence Technology and Applications, 2022. [paper]
  • Payam J. Yazdian, Mo Chen, and Angelica Lim, “Gesture2vec: Clustering gestures using representation learning methods for co-speech gesture generation,” in International Conference on Intelligent Robots and Systems, Best Paper Award on Cognitive Robotics, 2022 [paper | demo video | presentation]
  • Saba Akhyani, Mehryar Abbasi, Mo Chen, and Angelica Lim, “Towards inclusive HRI: Using sim2real to address under representation in emotion expression recognition,” in International Conference on Intelligent Robots and Systems, 2022 [paper]
  • Sahar Leisiazar, Mohammad Mahdavian, Edward J. Park, and Mo Chen, “Real-time mapping of multi-floor buildings using elevators,” in International Conference on Advanced Intelligent Mechatronics, 2022 [paper | video]
  • Pedram Agand, Mahdi Taherahmadi, Angelica Lim, and Mo Chen, “Human navigational intent inference with probabilistic and optimal approaches,” in International Conference on Robotics and Automation, 2022 [paper]
  • Atefeh Sahraee and Mo Chen, “PA-FaSTrack: Planner-Aware Real-Time Guaranteed Safe Planning,” in Conference on Decision and Control, 2021 [paper]
  • Minh Bui, Michael Lu, Reza Hojabr, Mo Chen, and Arrvindh Shriraman, “Real-Time Formal Verification of Autonomous Systems With An FPGA,” in International Conference on Intelligent Robots and Systems, 2021 [paper | video]
  • Zhitian Zhang, Jimin Rhim, Angelica Lim, and Mo Chen, “A Multimodal and Hybrid Framework for Human Navigational Intent Inference,” in International Conference on Intelligent Robots and Systems, 2021 [paper]
  • Anjian Li, Liting Sun, Wei Zhan, Masayoshi Tomizuka, and Mo Chen, “Prediction-Based Reachability for Collision Avoidance in Autonomous Driving,” in International Conference on Robotics and Automation, 2021 [paper]
  • Payam Nikdel, Richard Vaughan, and Mo Chen, “LBGP: Learning Based Goal Planning for Autonomous Following in Front,” in International Conference on Robotics and Automation, 2021 [paper]
  • Payam Nikdel, Mo Chen, and Richard Vaughan, “Recognizing and Tracking High-Level, Human-Meaningful Navigation Features of Occupancy Grid Maps,” in Conference on Computer and Robot Vision, 2020
  • Anjian Li, Somil Bansal, George Giovanis, Varun Tolani, Claire J. Tomlin, and Mo Chen, “Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability,” in Learning for Dynamics & Control Conference, 2020 [paper]
  • Xubo Lyu and Mo Chen, “TTR-Based Reward for Reinforcement Learning with Implicit Model Priors,” in International Conference on Intelligent Robots and Systems, 2020
  • Seth Siriya, Minh Bui, Arrvindh Shriraman, Mo Chen, and Ye Pu, “Safety-Guaranteed Real-Time Trajectory Planning for Underwater Vehicles in Plane-Progressive Waves,” in Conference on Decision and Control, 2020
  • Juan Chacon, Mo Chen, and Razvan C. Fetecau, “Safe Coverage of Compact Domains For Second Order Dynamical Systems,” in IFAC World Congress, 2020
  • Anjian Li and Mo Chen, “Guaranteed-Safe Approximate Reachability via State Dependency-Based Decomposition,” in American Control Conference, 2019
  • Donggun Lee*, Mo Chen*, and Claire J. Tomlin, “Removing Leaking Corners to Reduce Dimensionality in Hamilton-Jacobi Reachability,” in International Conference on Robotics and Automation, 2019
  • Boris Ivanovic, James Harrison, Apoorva Sharma, Mo Chen, and Marco Pavone, “BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning,” in International Conference on Robotics and Automation, 2019
  • Mo Chen, Qizhan Tam, Scott C. Livingston, and Marco Pavone, “Signal Temporal Logic Meets Reachability: Connections and Applications,” in International Workshop on the Algorithmic Foundations of Robotics, 2018
  • Sumeet Singh, Mo Chen, Sylvia L. Herbert, Claire J. Tomlin, and Marco Pavone, “Robust Tracking with Model Mismatch for Fast and Safe Planning: An SOS Optimization Approach,” in International Workshop on the Algorithmic Foundations of Robotics, 2018
  • Haimin Hu, Ye Pu, Mo Chen, and Claire J. Tomlin, “Plug and Play Distributed Model Predictive Control for Heavy Duty Vehicle Platooning and Interaction with Passenger Vehicles,” in Conference on Decision and Control, 2018
  • Joe Lorenzetti, Mo Chen, Benoit Landry, and Marco Pavone, “Reach-Avoid Games Via Mixed-Integer Second-Order Cone Programming,” in Conference on Decision and Control, 2018
  • Benoit Landry, Mo Chen, Scott Hemley, and Marco Pavone, “Reach-Avoid Problems via Sum-or-Squares Optimization and Dynamic Programming,” in International Conference on Intelligent Robots and Systems, 2018
  • Karen Leung, Edward Schmerling, Mo Chen, John Talbot, Christian J. Gerdes, and Marco Pavone, “On Infusing Reachability-Based Safety Assurance Within Probabilistic Planning Frameworks for Human-Robot Vehicle Interactions,” in International Symposium on Experimental Robotics, 2018
  • Somil Bansal, Mo Chen, Jaime F. Fisac, and Claire J. Tomlin, “Safe sequential path planning under disturbances and imperfect information,” in American Control Conference, 2017
  • Aparna Dhinakaran*, Mo Chen*, Glen Chou, Jennifer C. Shih, and Claire J. Tomlin, “A hybrid framework for multi-vehicle collision avoidance,” in Conference on Decision and Control, 2017
  • Mo Chen, Sylvia L. Herbert, and Claire J. Tomlin, “Exact and efficient Hamilton-Jacobi guaranteed safety analysis via system decomposition,” in International Conference on Robotics and Automation, 2017
  • Sylvia L. Herbert, Mo Chen, SooJean Han, Somil Bansal, Jaime F. Fisac, and Claire J. Tomlin, “FaSTrack: A modular framework for fast and guaranteed safe motion planning,” in Conference on Decision and Control, 2017
  • Somil Bansal*, Mo Chen*, Sylvia L. Herbert*, and Claire J. Tomlin, “Hamilton-Jacobi reachability: A brief overview and recent advances,” in Conference on Decision and Control, 2017
  • Mo Chen, Sylvia L. Herbert, and Claire J. Tomlin, “Fast reachable set approximations via state decoupling disturbances,” in Conference on Decision and Control, 2016
  • Mo Chen, Jennifer C. Shih, and Claire J. Tomlin, “Multi-vehicle collision avoidance via Hamilton-Jacobi reachability and mixed integer programming,” in Conference on Decision and Control, 2016
  • Mo Chen and Claire J. Tomlin, “Exact and efficient Hamilton-Jacobi reachability for decoupled systems,” in Conference on Decision and Control, 2015
  • Mo Chen, Qie Hu, Casey Mackin, Jaime F. Fisac, and Claire J. Tomlin, “Safe platooning of unmanned aerial vehicles via reachability,” in Conference on Decision and Control, 2015
  • Mo Chen, Jaime F. Fisac, S. Sastry, and Claire J. Tomlin, “Safe sequential path planning of multi-vehicle systems via double-obstacle Hamilton-Jacobi-Isaacs variational inequality,” in European Control Conference, 2015
  • Jaime F. Fisac, Mo Chen, Claire J. Tomlin, and S. S. Sastry, “Reach-avoid problems with time-varying dynamics, targets and constraints,” in International Conference on Hybrid Systems Computation and Control, 2015
  • Young Hwan Chang, Mo Chen, Maryam Shanechi, Jose M. Carmena, and Claire J. Tomlin, “A design of neural decoder by reducing discrepancy between Manual Control (MC) and Brain Control (BC),” in European Control Conference, 2014
  • Junkai Lu, Mo Chen, Young Hwan Chang, Masayoshi Tomizuka, Jose M. Carmena, and Claire J. Tomlin, “Design of a neural decoder by sensory prediction and error correction,” in Conference on Decision and Control, 2014
  • Mo Chen, Zhengyuan Zhou, and Claire J. Tomlin, “A path defense approach to the multiplayer reach-avoid game,” in Conference on Decision and Control, 2014
  • Mo Chen, Zhengyuan Zhou, and Claire J. Tomlin, “Multiplayer reach-avoid games via low dimensional solutions and maximum matching,” in American Control Conference, 2014
  • Maximillian Balandat, Frauke Oldewurtel, Mo Chen, and Claire J. Tomlin, “Contract design for frequency regulation by aggregations of commercial buildings,” in Allerton Conference on Communication, Control, and Computing, 2014
  • Young Hwan Chang, Mo Chen, Suraj Gowda, Simon A. Overduin, Jose M. Carmena, and Claire J. Tomlin, “Low-rank representation of neural activity and detection of submovements,” in Conference on Decision and Control, 2013
  • Ian M. Mitchell, Mo Chen, and Meeko Oishi, “Ensuring Safety of Nonlinear Sampled Data Systems through Reachability,” IFAC Proceedings Volumes, vol. 45, no. 9, pp. 108–114, 2012

* indicates equal lead authors