See full list of publications and citations on my google scholar page. Preprint
Joint Sampling and Trajectory Optimization over Graphs for Online Motion Planning
Kalyan Vasudev Alwala, & Mustafa Mukadam arXiv:2011.07171, 2020
Batteries, camera, action! Learning a semantic control space for expressive robot cinematography Rogerio Bonatti, Arthur Bucker, Sebastian Scherer, Mustafa Mukadam, & Jessica Hodgins arXiv:2011.10118, 2020
[arxiv][video]
2020
Neural Dynamic Policies for End-to-End Sensorimotor Learning Shikhar Bahl, Mustafa Mukadam, Abhinav Gupta, & Deepak Pathak Neural Information Processing Systems (NeurIPS), 2020 Spotlight, 3% Acceptance Rate
RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, & Nathan Ratliff Transactions on Automation Science and Engineering (T-ASE), 2020 Invited Paper
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm Giovanni Sutanto, Austin Wang, Yixin Lin, Mustafa Mukadam, Gaurav Sukhatme, Akshara Rai, & Franziska Meier Learning for Dynamics and Control (L4DC), 2020
Differentiable Gaussian Process Motion Planning Mohak Bhardwaj, Byron Boots, & Mustafa Mukadam International Conference on Robotics and Automation (ICRA), 2020
2019
Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping Mustafa Mukadam, Ching-An Cheng, Dieter Fox, Byron Boots, & Nathan Ratliff Conference on Robot Learning (CoRL), 2019
Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations Asif Rana*, Anqi Li*, Harish Ravichandar, Mustafa Mukadam, Sonia Chernova, Dieter Fox, Byron Boots, & Nathan Ratliff Conference on Robot Learning (CoRL), 2019
Multi-Objective Policy Generation for Multi-Robot Systems Using Riemannian Motion Policies Anqi Li, Mustafa Mukadam, Magnus Egerstedt, & Byron Boots International Symposium on Robotics Research (ISRR), 2019
Structured Learning and Inference for Robot Motion Generation Ph.D. Dissertation, Georgia Institute of Technology, 2019 Online Motion Planning Over Multiple Homotopy Classes with Gaussian Process Inference Keshav Kolur*, Sahit Chintalapudi*, Byron Boots, & Mustafa Mukadam International Conference on Intelligent Robots and Systems (IROS), 2019 Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing Alexander Lambert, Mustafa Mukadam, Balakumar Sundaralingam, Nathan Ratliff, Byron Boots, & Dieter Fox. International Conference on Robotics and Automation (ICRA), 2019
RMPflow: A Computational Graph for Automatic Motion Policy Generation Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, & Nathan Ratliff International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018 Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments Asif Rana, Mustafa Mukadam, Reza Ahmadzadeh, Sonia Chernova, & Byron Boots International Conference on Intelligent Robots and Systems (IROS), 2018 STEAP: Simultaneous Trajectory Estimation and Planning Mustafa Mukadam*, Jing Dong*, Frank Dellaert, & Byron Boots Autonomous Robots (AuRo), 2018 Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference Mustafa Mukadam*, Jing Dong*, Xinyan Yan, Frank Dellaert, & Byron Boots International Journal of Robotics Research (IJRR), 2018 Winner of IJRR Paper of the Year Award Sparse Gaussian Processes on Matrix Lie Groups: A Unified Framework for Optimizing Continuous-Time Trajectories Jing Dong, Mustafa Mukadam, Byron Boots, & Frank Dellaert International Conference on Robotics and Automation (ICRA), 2018
Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning Asif Rana, Mustafa Mukadam, Reza Ahmadzadeh, Sonia Chernova, & Byron Boots Conference on Robot Learning (CoRL), 2017 Long Talk, 8% Acceptance Rate Simultaneous Trajectory Estimation and Planning via Probabilistic Inference Mustafa Mukadam, Jing Dong, Frank Dellaert, & Byron Boots Robotics: Science and Systems (RSS), 2017 Approximately Optimal Continuous-Time Motion Planning and Control via Probabilistic Inference Mustafa Mukadam, Ching-An Cheng, Xinyan Yan, & Byron Boots International Conference on Robotics and Automation (ICRA), 2017 Motion Planning with Graph-Based Trajectories and Gaussian Process Inference Eric Huang, Mustafa Mukadam, Zhen Liu, & Byron Boots International Conference on Robotics and Automation (ICRA), 2017
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs Jing Dong, Mustafa Mukadam, Frank Dellaert, & Byron Boots Robotics: Science and Systems (RSS), 2016 Gaussian Process Motion Planning Mustafa Mukadam, Xinyan Yan, & Byron Boots International Conference on Robotics and Automation (ICRA), 2016
Quasi-static Manipulation of a Planar Elastic Rod using Multiple Robotic Grippers Mustafa Mukadam, Andy Borum, & Timothy Bretl International Conference on Intelligent Robots and Systems (IROS), 2014
Autonomous Vehicle Policy Generation Mustafa Mukadam, Akansel Cosgun, Alireza Nakhaei, & Kikuo Fujimura US Patent 10,739,776 B2, 2020
Interaction-Aware Planning via Nash Equilibria for Manipulation in a Shared Workspace Shray Bansal, Mustafa Mukadam, & Charles Isbell ICRA Workshop on Human Movement Science for Physical Human-Robot Collaboration, 2019 Tactical Decision Making for Lane Changing with Deep Reinforcement Learning Mustafa Mukadam, Akansel Cosgun, Alireza Nakhaei, & Kikuo Fujimura NIPS Workshop on Machine Learning for Intelligent Transportation Systems, 2017
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