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09/21/2023
Uncertainty-driven Exploration Strategies for Online Grasp Learning
Existing grasp prediction approaches are mostly based on offline learnin...
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08/01/2023
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes
Robotic grasping is a fundamental skill required for object manipulation...
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07/31/2023
Model-free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking
This paper presents a novel method for model-free prediction of grasp po...
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07/01/2023
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation
Detecting objects and estimating their 6D poses is essential for automat...
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11/20/2022
Multi-Arm Bin-Picking in Real-Time: A Combined Task and Motion Planning Approach
Automated bin-picking is a prerequisite for fully automated manufacturin...
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10/18/2022
Deep Black-Box Reinforcement Learning with Movement Primitives
-based reinforcement learning (ERL) algorithms treat reinforcement learn...
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09/22/2022
FusionVAE: A Deep Hierarchical Variational Autoencoder for RGB Image Fusion
Sensor fusion can significantly improve the performance of many computer...
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03/09/2022
What Matters For Meta-Learning Vision Regression Tasks?
Meta-learning is widely used in few-shot classification and function reg...
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02/28/2022
Hierarchical Policy Learning for Mechanical Search
Retrieving objects from clutters is a complex task, which requires multi...
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11/02/2021
A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitives
Many possible fields of application of robots in real world settings hin...
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08/03/2021
Non-local Graph Convolutional Network for joint Activity Recognition and Motion Prediction
3D skeleton-based motion prediction and activity recognition are two int...
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06/10/2021
Differentiable Robust LQR Layers
This paper proposes a differentiable robust LQR layer for reinforcement ...
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06/08/2021
Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty
While classic control theory offers state of the art solutions in many p...
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01/22/2021
Differentiable Trust Region Layers for Deep Reinforcement Learning
Trust region methods are a popular tool in reinforcement learning as the...
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02/20/2020
Deep Energy Autoencoder for Noncoherent Multicarrier MU-SIMO Systems
We propose a novel deep energy autoencoder (EA) for noncoherent multicar...
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05/11/2018
Deep Hierarchical Reinforcement Learning Algorithm in Partially Observable Markov Decision Processes
In recent years, reinforcement learning has achieved many remarkable suc...
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04/13/2018
