Fábio Ferreira — accepted AI-conference papers

2020

UniGrasp: Learning a Unified Model to Grasp With Multifingered Robotic Hands

Lin Shao, Fábio Ferreira, Mikael Jorda, Varun Nambiar, Jianlan Luo, Eugen Solowjow +3

RA-L 2020

To achieve a successful grasp, gripper attributes such as its geometry and kinematics play a role as important as the object geometry. The majority of previous work has focused on developing grasp methods that generalize over novel object geometry but are specific to a certain robot hand. We propose

Cited by 138 Source ↗code ↗Scholar ↗

2018

Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution

Jonas Rothfuss, Fábio Ferreira, Eren Erdal Aksoy, You Zhou, Tamim Asfour

RA-L 2018

We present a novel deep neural network architecture for representing robot experiences in an episodic-like memory that facilitates encoding, recalling, and predicting action experiences. Our proposed unsupervised deep episodic memory model as follows: First, encodes observed actions in a latent vect

Cited by 39 Source ↗code ↗Scholar ↗