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CoRAL Lab Publications

Preprints

  • Model-free Neural Lyapunov Control for Safe Robot Navigation
    Z.Xiong, J.Eappen, A.H.Qureshi, and S.Jagannathan
    arXiv:2203.01190 [cs.RO] [arXiv]

  • Motion Planning Transformers: One Model to Plan Them All
    J.J.Johnson, L.Li, A.H.Qureshi, and M.C.Yip
    arXiv:2106.02791 [cs.RO] [arXiv]

2021

  • NeRP: Neural Rearrangement Planning for Unknown Objects
    A.H.Qureshi, A.Mousavian, C.Paxton, M.C.Yip, and D.Fox
    Robotics: Science and Systems, 2021. [paper] [arXiv] [project]


  • Constrained Motion Planning Networks X
    A.H.Qureshi, J.Dong, A.Baig, and M.C.Yip
    IEEE Transactions on Robotics, 2021. [paper] [arXiv] [project]


  • MPC-MPNet: Model-Predictive Motion Planning Networks for Fast, Near-Optimal Planning under Kinodynamic Constraints
    L.Li, Y.Miao, A.H.Qureshi, and M.C.Yip
    IEEE Robotics and Automation Letters, 2021. [paper] [arXiv] [project]

2020

  • Neural Manipulation Planning on Constraint Manifolds
    A.H.Qureshi, J.Dong, A.Choe, and M.C.Yip
    IEEE Robotics and Automation Letters, 2020. [paper] [arXiv] [project]


  • Composing TaskAgnostic Policies via Deep Reinforcement Learning
    A.H.Qureshi, J.J.Johnson, Y.Qin, T.West, B.Boots, and M.C.Yip
    International Conference on Representation Learning (ICLR), 2020. [paper] [arXiv] [project]


  • Dynamically Constrained Motion Planning Networks for Non-Holonomic Robots
    J.Johnson, L.Li, F.Liu, A.H.Qureshi, and M.C.Yip
    IEEE/RSJ International Conference on Intelligent Robot and Systems (IROS), 2020. [paper] [arXiv] [project]


  • Active Continual Learning for Planning and Navigation
    A.H.Qureshi, Y.Miao, and M.C.Yip
    ICML Workshop on Real World Experiment Design and Active Learning, 2020


  • Motion Planning Networks: Bridging the Gap Between Learning-based and Classical Motion Planners
    A.H.Qureshi, Y.Miao, A.Simeonov, and M.C.Yip
    IEEE Transactions on Robotics, 2020. [paper] [arXiv] [project]


2019

  • Adversarial Imitation Via Variational Inverse Reinforcement Learning
    A.H.Qureshi, B. Boots, and M.C.Yip
    International Conference on Representation Learning (ICLR), 2019. [paper] [arXiv] [project]


  • Motion Planning Networks
    A.H.Qureshi, A.Simeonov, M.J.Bency, and M.C.Yip
    IEEE/RAS International Conference on Robotics and Automation (ICRA), 2019. [paper] [arXiv] [project]


  • Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation
    M.J.Bency, A.H.Qureshi, and M.C.Yip
    IEEE/RSJ International Conference on Intelligent Robot and Systems (IROS), 2019. [paper] [arXiv] [project]


  • Machine Learning based Fixed-Time Optimal Path Generation
    M.C.Yip, M.J.Bency, and A.H.Qureshi
    US Patent App. 16/222,706, 2019. [paper]


2018

  • Intrinsically motivated reinforcement learning for human–robot interaction in the real-world
    A.H.Qureshi, Y.Nakamura, Y.Yoshikawa, and H.Ishiguro
    Neural Networks, 2018. [paper] [arXiv]


  • Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments
    Z.Tahir, A.H.Qureshi, Y.Ayaz, and R.Nawaz
    International Journal of Robotics and Autonomous Systems, 2018. [paper] [arXiv]


  • Deeply Informed Neural Sampling For Robot Motion Planning
    A.H.Qureshi and M.C.Yip
    IEEE/RSJ International Conference on Intelligent Robot and Systems (IROS), 2018. [paper] [arXiv]


  • Adversarial Reward and Policy learning Via Variational Inverse Optimal Control
    A.H.Qureshi, and M.C.Yip
    Bay Area Machine Learning Symposium, 2018.


  • Re-planning Using Delaunay Triangulation for Real Time Motion Planning in Complex Dynamic Environments
    A.H.Qureshi, Z.Tahir, G.Tariq, and Y.Ayaz
    IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2018. [paper]


2017

  • Deep reinforcement learning for human-robot interaction in the real-world
    A.H.Qureshi
    M.S. Thesis, Osaka University, 2017. [paper]


  • Show, Attend and Interact: Perceivable Social Human-Robot Interaction through Neural Attention Q-Network
    A.H.Qureshi, Y.Nakamura, Y.Yoshikawa, and H.Ishiguro
    IEEE/RAS International Conference on Robotics and Automation (ICRA), 2017. [paper] [arXiv]


2016

  • Robot gains social intelligence through multimodal deep reinforcement learning
    A.H.Qureshi, Y.Nakamura, Y.Yoshikawa, and H.Ishiguro
    IEEE/RAS International Conference on Humanoid Robots, 2016. [paper] [arXiv]


  • Robot Learns Responsive Behavior through Interaction with People using Deep Reinforcement Learning
    A.H.Qureshi, Y.Nakamura, Y.Yoshikawa, and H.Ishiguro
    International Symposium on Cognitive Neuroscience Robotics, 2016.


2015

  • Potential Functions Based Sampling Heuristic for Optimal Motion Planning
    A.H.Qureshi and Y.Ayaz
    Autonomous Robots, 2015. [paper] [arXiv]


  • Intelligent Bidirectional Rapidly-Exploring Random Trees for Optimal Motion Planning in Complex Cluttered Environments
    A.H.Qureshi and Y.Ayaz
    International Journal of Robotics and Autonomous Systems, 2015. [paper] [arXiv]


  • Triangular Geometrised Sampling Heuristic For RRT* Motion Planner
    A.H.Qureshi, S.Mumtaz, Y.Ayaz, O.Hasan, M.S.Muhammad, and M.T.Mahmood
    International Journal of Advanced Robotic Systems (IJARS), 2015. [paper]


  • Collaborative optimal reciprocal collision avoidance for mobile robots
    S.A.Khan, Y.Ayaz, M.Jamil, S.O.Gillani, M.Naveed, A.H.Qureshi, and K.FIqbal
    Journal of Control and Automation, 2015. [paper]


2014

  • Augmenting RRT*-Planner with Local Trees for Motion Planning in Complex Dynamic Environments
    A.H.Qureshi, S.Mumtaz, Y. Ayaz, and O. Hasan
    IEEE/RAS International Conference on Methods and Models in Automation and Robotics (MMAR), 2014. [paper]


  • Enhanced RRT* for Motion Planning in Complex Cluttered Environments
    A.H.Qureshi, and S.Mumtaz
    B.S. Thesis, NUST, 2014.


2013

  • Adaptive Potential Guided Directional RRT*
    A.H.Qureshi, S.Mumtaz, Y.Ayaz, O.Hasan, and W.Y.Kim
    IEEE/RAS International Conference on Robotics and Biomimetics (ROBIO), 2013. [paper]


  • Human tracking by a mobile robot using 3D features
    B.Ali, A.H.Qureshi, Y.Ayaz, N.Muhammad, and W.Y.Kim
    IEEE/RAS International Conference on Robotics and Biomimetics (ROBIO), 2013. [paper]


  • Potential guided directional-RRT* for accelerated motion planning in cluttered environments
    A.H.Qureshi, K.F.Iqbal, S.M.Qamar, F.Islam, Y.Ayaz, and N.Muhammad
    IEEE/RAS International Conference on Mechatronics and Automation (ICMA), 2013. [paper]


  • A solution to Perceptual Aliasing through Probabilistic Fuzzy Logic and SIFT
    S.M.Qamar, K.F.Iqbal, A.H.Qureshi, N.Muhammad, Y.Ayaz, and A.G.Abbasi
    IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2013. [paper]