See full list of publications and citations on my google scholar page.

Preprint

  • Habitat 2.0: Training Home Assistants to Rearrange their Habitat

Andrew Szot, Alex Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John Turner, Noah Maestre, Mustafa Mukadam, Devendra Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, & Dhruv Batra

arXiv:2106.14405, 2021

[arxiv][webpage][code]

2021

  • A Differentiable Recipe for Learning Visual Dexterous Planar Manipulation

Bernardo Aceituno, Alberto Rodriguez, Shubham Tulsiani, Abhinav Gupta, & Mustafa Mukadam

Conference on Robot Learning (CoRL), 2021

[pdf coming soon]

  • LEO: Learning Energy-based Models in Graph Optimization

Paloma Sodhi, Eric Dexheimer, Mustafa Mukadam, Stuart Anderson, & Michael Kaess

Conference on Robot Learning (CoRL), 2021

[arxiv][video][webpage][code]

  • Taskography: Evaluating robot task planning over large 3D scene graphs

Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, & Florian Shkurti

Conference on Robot Learning (CoRL), 2021

[pdf coming soon]

  • Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation

Taosha Fan, Kalyan Vasudev Alwala, Donglai Xiang, Weipeng Xu, Todd Murphey, & Mustafa Mukadam

International Conference on Computer Vision (ICCV), 2021

[arxiv][video][webpage][code]

  • Where2Act: From Pixels to Actions for Articulated 3D Objects

Kaichun Mo, Leonidas Guibas, Mustafa Mukadam, Abhinav Gupta, & Shubham Tulsiani

International Conference on Computer Vision (ICCV), 2021

[arxiv][webpage][code]

  • Joint Sampling and Trajectory Optimization over Graphs for Online Motion Planning

Kalyan Vasudev Alwala, & Mustafa Mukadam

International Conference on Intelligent Robots and Systems (IROS), 2021

[arxiv][video][webpage][code]

  • Learning Tactile Models for Factor Graph-based Estimation

Paloma Sodhi, Michael Kaess, Mustafa Mukadam, & Stuart Anderson

International Conference on Robotics and Automation (ICRA), 2021

[arxiv][video][webpage][code]

  • Batteries, camera, action! Learning a semantic control space for expressive robot cinematography

Rogerio Bonatti, Arthur Bucker, Sebastian Scherer, Mustafa Mukadam, & Jessica Hodgins

International Conference on Robotics and Automation (ICRA), 2021

[arxiv][video][webpage]

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

[pdf][arxiv][video][code]

  • 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

[arxiv]

  • 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

[pdf][arxiv]

  • Differentiable Gaussian Process Motion Planning

Mohak Bhardwaj, Byron Boots, & Mustafa Mukadam

International Conference on Robotics and Automation (ICRA), 2020

[arxiv][talk][code]

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

[pdf][arxiv][video][talk]

  • 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

[pdf][video]

  • 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

[arxiv][video]

  • Structured Learning and Inference for Robot Motion Generation

Mustafa Mukadam

Ph.D. Dissertation, Georgia Institute of Technology, 2019

[pdf]

  • 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

[arxiv][video]

  • 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

[arxiv][video]

2018

  • 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

[arxiv][video]

  • 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

[arxiv][video]

  • STEAP: Simultaneous Trajectory Estimation and Planning

Mustafa Mukadam*, Jing Dong*, Frank Dellaert, & Byron Boots

Autonomous Robots (AuRo), 2018

Invited Paper

[pdf][arxiv]

  • 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

[pdf][arxiv]

  • 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

[pdf]

2017

  • 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

[pdf][video][talk][code]

  • Simultaneous Trajectory Estimation and Planning via Probabilistic Inference

Mustafa Mukadam, Jing Dong, Frank Dellaert, & Byron Boots

Robotics: Science and Systems (RSS), 2017

[pdf][code][video][slides]

  • 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

[arxiv][video]

  • 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

[pdf][video]

2016

  • 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

[pdf][code][video][talk]

  • Gaussian Process Motion Planning

Mustafa Mukadam, Xinyan Yan, & Byron Boots

International Conference on Robotics and Automation (ICRA), 2016

[pdf][video]

2014

  • 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

[pdf][video]

Patent

  • Autonomous Vehicle Policy Generation

Mustafa Mukadam, Akansel Cosgun, Alireza Nakhaei, & Kikuo Fujimura

US Patent 10,739,776 B2, 2020

[pdf]

Refereed Workshop

  • 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

[pdf]

  • 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

[pdf]