Search Results for author: Tucker Hermans

Found 21 papers, 4 papers with code

DULA and DEBA: Differentiable Ergonomic Risk Models for Postural Assessment and Optimization in Ergonomically Intelligent pHRI

no code implementations6 May 2022 Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather, Tucker Hermans

In order to retain assessment quality, while improving computational considerations, we propose a novel framework for postural assessment and optimization for ergonomically intelligent physical human-robot interaction.

L4KDE: Learning for KinoDynamic Tree Expansion

no code implementations2 Mar 2022 Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos

We study the kinodynamic variants of tree-based planning, where we have known system dynamics and kinematic constraints.

Motion Planning

StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objects

no code implementations19 Oct 2021 Weiyu Liu, Chris Paxton, Tucker Hermans, Dieter Fox

Geometric organization of objects into semantically meaningful arrangements pervades the built world.

Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Clouds

no code implementations10 Oct 2021 Bao Thach, Brian Y. Cho, Alan Kuntz, Tucker Hermans

If robots could reliably manipulate the shape of 3D deformable objects, they could find applications in fields ranging from home care to warehouse fulfillment to surgical assistance.

Visual Servo

Predicting Stable Configurations for Semantic Placement of Novel Objects

1 code implementation26 Aug 2021 Chris Paxton, Chris Xie, Tucker Hermans, Dieter Fox

We further demonstrate the ability of our planner to generate and execute diverse manipulation plans through a set of real-world experiments with a variety of objects.

Motion Planning

Ergonomically Intelligent Physical Human-Robot Interaction: Postural Estimation, Assessment, and Optimization

no code implementations12 Aug 2021 Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather, Tucker Hermans

We use DULA in postural optimization for physical human-robot interaction tasks such as co-manipulation and teleoperation.

DeformerNet: A Deep Learning Approach to 3D Deformable Object Manipulation

no code implementations16 Jul 2021 Bao Thach, Alan Kuntz, Tucker Hermans

In this paper, we propose a novel approach to 3D deformable object manipulation leveraging a deep neural network called DeformerNet.

Deformable Object Manipulation

DULA: A Differentiable Ergonomics Model for Postural Optimization in Physical HRI

no code implementations14 Jul 2021 Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather, Tucker Hermans

Ergonomics and human comfort are essential concerns in physical human-robot interaction applications.

Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls

no code implementations8 Jan 2021 Sarvenaz Chaeibakhsh, Roya Sabbagh Novin, Tucker Hermans, Andrew Merryweather, Alan Kuntz

In this work, we formulate a gradient-free constrained optimization problem to generate and reconfigure the hospital room interior layout to minimize the risk of falls.

Planning under Uncertainty to Goal Distributions

1 code implementation9 Nov 2020 Adam Conkey, Tucker Hermans

We argue that goal distributions are a more appropriate goal representation than deterministic sets for many robotics applications.

Robotics

Multi-Fingered Active Grasp Learning

no code implementations6 Jun 2020 Qingkai Lu, Mark Van der Merwe, Tucker Hermans

We show that our active grasp learning approach uses fewer training samples to produce grasp success rates comparable with the passive supervised learning method trained with grasping data generated by an analytical planner.

Robotics

In-Hand Object-Dynamics Inference using Tactile Fingertips

1 code implementation30 Mar 2020 Balakumar Sundaralingam, Tucker Hermans

We show that tactile fingertips enable in-hand dynamics estimation of low mass objects.

Robotics

Is The Leader Robot an Adequate Sensor for Posture Estimation and Ergonomic Assessment of A Human Teleoperator?

no code implementations24 Feb 2020 Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather, Tucker Hermans

Ergonomic assessment of human posture plays a vital role in understanding work-related safety and health.

Robotics Human-Computer Interaction Signal Processing

Multi-Fingered Grasp Planning via Inference in Deep Neural Networks

no code implementations25 Jan 2020 Qingkai Lu, Mark Van der Merwe, Balakumar Sundaralingam, Tucker Hermans

We can then formulate grasp planning as inferring the grasp configuration which maximizes the probability of grasp success.

Robotics

Benchmarking In-Hand Manipulation

no code implementations9 Jan 2020 Silvia Cruciani, Balakumar Sundaralingam, Kaiyu Hang, Vikash Kumar, Tucker Hermans, Danica Kragic

The purpose of this benchmark is to evaluate the planning and control aspects of robotic in-hand manipulation systems.

Robotics

Learning Continuous 3D Reconstructions for Geometrically Aware Grasping

no code implementations2 Oct 2019 Mark Van der Merwe, Qingkai Lu, Balakumar Sundaralingam, Martin Matak, Tucker Hermans

We leverage the structure of the reconstruction network to learn a grasp success classifier which serves as the objective function for a continuous grasp optimization.

3D Reconstruction Common Sense Reasoning

Learning to Manipulate Object Collections Using Grounded State Representations

1 code implementation17 Sep 2019 Matthew Wilson, Tucker Hermans

We propose a method for sim-to-real robot learning which exploits simulator state information in a way that scales to many objects.

Active Learning of Probabilistic Movement Primitives

no code implementations29 Jun 2019 Adam Conkey, Tucker Hermans

However, there is currently no principled guidance in the literature to determine how many demonstrations a teacher should provide and what constitutes a "good" demonstration for promoting generalization.

Robotics

Building 3D Object Models during Manipulation by Reconstruction-Aware Trajectory Optimization

no code implementations10 May 2019 Kanrun Huang, Tucker Hermans

We use a sampling-based trajectory generation method to explore the unseen parts of the object using the estimated conditional entropy of the GPIS model.

3D Object Reconstruction

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