Search Results for author: Mark Van der Merwe

Found 8 papers, 2 papers with code

Integrated Object Deformation and Contact Patch Estimation from Visuo-Tactile Feedback

no code implementations23 May 2023 Mark Van der Merwe, Youngsun Wi, Dmitry Berenson, Nima Fazeli

Representing the object geometry and contact with the environment implicitly allows a single model to predict contact patches of varying complexity.

Object

Visuo-Tactile Transformers for Manipulation

1 code implementation30 Sep 2022 Yizhou Chen, Andrea Sipos, Mark Van der Merwe, Nima Fazeli

Learning representations in the joint domain of vision and touch can improve manipulation dexterity, robustness, and sample-complexity by exploiting mutual information and complementary cues.

Model-based Reinforcement Learning Representation Learning

Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching

no code implementations5 Mar 2021 Tu-Hoa Pham, William Seto, Shreyansh Daftry, Barry Ridge, Johanna Hansen, Tristan Thrush, Mark Van der Merwe, Gerard Maggiolino, Alexander Brinkman, John Mayo, Yang Cheng, Curtis Padgett, Eric Kulczycki, Renaud Detry

This work informs the Mars Sample Return campaign on the choice of a site where Perseverance (R0) will place a set of sample tubes for future retrieval by another rover (R1).

Retrieval

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

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

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 +1

Message Scheduling for Performant, Many-Core Belief Propagation

1 code implementation24 Sep 2019 Mark Van der Merwe, Vinu Joseph, Ganesh Gopalakrishnan

Belief Propagation (BP) is a message-passing algorithm for approximate inference over Probabilistic Graphical Models (PGMs), finding many applications such as computer vision, error-correcting codes, and protein-folding.

Protein Folding Scheduling

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