Jeffrey Mahler

Orcid: 0000-0003-3204-3024

According to our database1, Jeffrey Mahler authored at least 36 papers between 2014 and 2021.

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Bibliography

2021
Partial caging: a clearance-based definition, datasets, and deep learning.
Auton. Robots, 2021

2020
Minimal Work: A Grasp Quality Metric for Deformable Hollow Objects.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Industrial Robot Grasping with Deep Learning using a Programmable Logic Controller (PLC).
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

Non-Markov Policies to Reduce Sequential Failures in Robot Bin Picking.
Proceedings of the 16th IEEE International Conference on Automation Science and Engineering, 2020

2019
On-Policy Dataset Synthesis for Learning Robot Grasping Policies Using Fully Convolutional Deep Networks.
IEEE Robotics Autom. Lett., 2019

REACH: Reducing False Negatives in Robot Grasp Planning with a Robust Efficient Area Contact Hypothesis Model.
Proceedings of the Robotics Research, 2019

Partial Caging: A Clearance-Based Definition and Deep Learning.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data.
Proceedings of the International Conference on Robotics and Automation, 2019

Adversarial Grasp Objects.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

Dex-Net MM: Deep Grasping for Surface Decluttering with a Low-Precision Mobile Manipulator.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

Robust Toppling for Vacuum Suction Grasping.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2018
Efficient Policy Learning for Robust Robot Grasping.
PhD thesis, 2018

Guest Editorial Open Discussion of Robot Grasping Benchmarks, Protocols, and Metrics.
IEEE Trans Autom. Sci. Eng., 2018

Synthesis of Energy-Bounded Planar Caging Grasps Using Persistent Homology.
IEEE Trans Autom. Sci. Eng., 2018

Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Point Clouds.
CoRR, 2018

Dex-Net 3.0: Computing Robust Vacuum Suction Grasp Targets in Point Clouds Using a New Analytic Model and Deep Learning.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Dex-Net as a Service (DNaaS): A Cloud-Based Robust Robot Grasp Planning System.
Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

Linear Push Policies to Increase Grasp Access for Robot Bin Picking.
Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

2017
Dex-Net 3.0: Computing Robust Robot Suction Grasp Targets in Point Clouds using a New Analytic Model and Deep Learning.
CoRR, 2017

Iterative Noise Injection for Scalable Imitation Learning.
CoRR, 2017

Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics.
Proceedings of the Robotics: Science and Systems XIII, 2017

A cloud robot system using the dexterity network and berkeley robotics and automation as a service (Brass).
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Design of parallel-jaw gripper tip surfaces for robust grasping.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning Deep Policies for Robot Bin Picking by Simulating Robust Grasping Sequences.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

An algorithm for transferring parallel-jaw grasps between 3D mesh subsegments.
Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

Using dVRK teleoperation to facilitate deep learning of automation tasks for an industrial robot.
Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

2016
Energy-Bounded Caging: Formal Definition and 2-D Energy Lower Bound Algorithm Based on Weighted Alpha Shapes.
IEEE Robotics Autom. Lett., 2016

Large-scale supervised learning of the grasp robustness of surface patch pairs.
Proceedings of the 2016 IEEE International Conference on Simulation, 2016

Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

SHIV: Reducing supervisor burden in DAgger using support vectors for efficient learning from demonstrations in high dimensional state spaces.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Privacy-preserving Grasp Planning in the Cloud.
Proceedings of the IEEE International Conference on Automation Science and Engineering, 2016

2015
GP-GPIS-OPT: Grasp planning with shape uncertainty using Gaussian process implicit surfaces and Sequential Convex Programming.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Multi-armed bandit models for 2D grasp planning with uncertainty.
Proceedings of the IEEE International Conference on Automation Science and Engineering, 2015

2014
Autonomous multilateral debridement with the Raven surgical robot.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression.
Proceedings of the 2014 IEEE International Conference on Automation Science and Engineering, 2014


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