Mustafa Mukadam

Orcid: 0000-0002-5683-1642

According to our database1, Mustafa Mukadam authored at least 52 papers between 2014 and 2024.

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Bibliography

2024
NeuralFeels with neural fields: Visuotactile perception for in-hand manipulation.
Sci. Robotics, 2024

Sparsh: Self-supervised touch representations for vision-based tactile sensing.
CoRR, 2024

A Touch, Vision, and Language Dataset for Multimodal Alignment.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation.
CoRR, 2023

Perceiving Extrinsic Contacts from Touch Improves Learning Insertion Policies.
CoRR, 2023

Learning to Read Braille: Bridging the Tactile Reality Gap with Diffusion Models.
CoRR, 2023

Decentralization and Acceleration Enables Large-Scale Bundle Adjustment.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

TaskMet: Task-driven Metric Learning for Model Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

USA-Net: Unified Semantic and Affordance Representations for Robot Memory.
IROS, 2023

Neural Grasp Distance Fields for Robot Manipulation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Neural Contact Fields: Tracking Extrinsic Contact with Tactile Sensing.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception.
Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Theseus: A Library for Differentiable Nonlinear Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

PatchGraph: In-hand tactile tracking with learned surface normals.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

In-Hand Gravitational Pivoting Using Tactile Sensing.
Proceedings of the Conference on Robot Learning, 2022

MidasTouch: Monte-Carlo inference over distributions across sliding touch.
Proceedings of the Conference on Robot Learning, 2022

2021
RMPflow: A Geometric Framework for Generation of Multitask Motion Policies.
IEEE Trans Autom. Sci. Eng., 2021

LEO: Learning Energy-based Models in Graph Optimization.
CoRR, 2021

Habitat 2.0: Training Home Assistants to Rearrange their Habitat.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

No RL, No Simulation: Learning to Navigate without Navigating.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Joint Sampling and Trajectory Optimization over Graphs for Online Motion Planning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Learning Tactile Models for Factor Graph-based Estimation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Batteries, camera, action! Learning a semantic control space for expressive robot cinematography.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Where2Act: From Pixels to Actions for Articulated 3D Objects.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

LEO: Learning Energy-based Models in Factor Graph Optimization.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Taskography: Evaluating robot task planning over large 3D scene graphs.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Learning Tactile Models for Factor Graph-based State Estimation.
CoRR, 2020

RMPflow: A Geometric Framework for Generation of Multi-Task Motion Policies.
CoRR, 2020

Neural Dynamic Policies for End-to-End Sensorimotor Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Encoding Physical Constraints in Differentiable Newton-Euler Algorithm.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Differentiable Gaussian Process Motion Planning.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019
Structured learning and inference for robot motion generation.
PhD thesis, 2019

STEAP: simultaneous trajectory estimation and planning.
Auton. Robots, 2019

Multi-objective Policy Generation for Multi-robot Systems Using Riemannian Motion Policies.
Proceedings of the Robotics Research, 2019

Online Motion Planning Over Multiple Homotopy Classes with Gaussian Process Inference.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing.
Proceedings of the International Conference on Robotics and Automation, 2019

Learning Reactive Motion Policies in Multiple Task Spaces from Human Demonstrations.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshaping.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018
Continuous-time Gaussian process motion planning via probabilistic inference.
Int. J. Robotics Res., 2018

RMPflow: A Computational Graph for Automatic Motion Policy Generation.
CoRR, 2018

RMP<i>flow</i>: A Computational Graph for Automatic Motion Policy Generation.
Proceedings of the Algorithmic Foundations of Robotics XIII, 2018

Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Sparse Gaussian Processes on Matrix Lie Groups: A Unified Framework for Optimizing Continuous-Time Trajectories.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017
Simultaneous Trajectory Estimation and Planning via Probabilistic Inference.
Proceedings of the Robotics: Science and Systems XIII, 2017

Approximately optimal continuous-time motion planning and control via Probabilistic Inference.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Motion planning with graph-based trajectories and Gaussian process inference.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs.
Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Gaussian Process Motion planning.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2014
Quasi-static manipulation of a planar elastic rod using multiple robotic grippers.
Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014


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