Ricardo V. Godoy

Orcid: 0000-0002-5323-9299

According to our database1, Ricardo V. Godoy authored at least 26 papers between 2019 and 2025.

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Bibliography

2025
A Synthetic Dataset for Manometry Recognition in Robotic Applications.
CoRR, August, 2025

Optimizing Grasping in Legged Robots: A Deep Learning Approach to Loco-Manipulation.
CoRR, August, 2025

Autonomous UAV Flight Navigation in Confined Spaces: A Reinforcement Learning Approach.
CoRR, August, 2025

A Vision-Based Shared-Control Teleoperation Scheme for Controlling the Robotic Arm of a Four-Legged Robot.
CoRR, August, 2025

MIHRaGe: A Mixed-Reality Interface for Human-Robot Interaction via Gaze-Oriented Control.
CoRR, May, 2025

Improving Failure Prediction in Aircraft Fastener Assembly Using Synthetic Data in Imbalanced Datasets.
CoRR, May, 2025

A Leaf-Level Dataset for Soybean-Cotton Detection and Segmentation.
CoRR, March, 2025

Offline Versus Real-Time Grasp Prediction Employing a Wearable High-Density Lightmyography Armband: On the Control of Prosthetic Hands.
IEEE Access, 2025

2024
Multi-Layer, Sensorized Kirigami Grippers for Delicate Yet Robust Robot Grasping and Single-Grasp Object Identification.
IEEE Access, 2024

Scalable, Fast, Highly-Accurate Human-to-Robot Skill Transfer for the Dexterous, Efficient Operation of Histology Microtomes.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

A Video Dataset of Everyday Life Grasps for the Training of Shared Control Operation Models for Myoelectric Prosthetic Hands.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

2023
Electromyography Based Gesture Decoding Employing Few-Shot Learning, Transfer Learning, and Training From Scratch.
IEEE Access, 2023

Scalable. Intuitive Human to Robot Skill Transfer with Wearable Human Machine Interfaces: On Complex, Dexterous Tasks.
IROS, 2023

Employing Multi-Layer, Sensorised Kirigami Grippers for Single-Grasp Based Identification of Objects and Force Exertion Estimation.
IROS, 2023

On Semi-Autonomous Robotic Telemanipulation Employing Electromyography Based Motion Decoding and Potential Fields.
IROS, 2023

An Affordances and Electromyography Based Telemanipulation Framework for Control of Robotic Arm-Hand Systems.
IROS, 2023

On Human Grasping and Manipulation in Kitchens: Automated Annotation, Insights, and Metrics for Effective Data Collection.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Multi-Grasp Classification for the Control of Robot Hands Employing Transformers and Lightmyography Signals.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

An Adaptive, Humanlike Prosthetic Hand Equipped with a Series Elastic Differential and a Lightmyography Based Control Interface.
Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023

Why, in Deep Learning, Non-smooth Activation Function Works Better Than Smooth Ones.
Proceedings of the Decision Making Under Uncertainty and Constraints - A Why-Book, 2023

2022
EEG-Based Epileptic Seizure Prediction Using Temporal Multi-Channel Transformers.
CoRR, 2022

On EMG Based Dexterous Robotic Telemanipulation: Assessing Machine Learning Techniques, Feature Extraction Methods, and Shared Control Schemes.
IEEE Access, 2022

Lightmyography Based Decoding of Human Intention Using Temporal Multi-Channel Transformers.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Comparing Human and Robot Performance in the Execution of Kitchen Tasks: Evaluating Grasping and Dexterous Manipulation Skills.
Proceedings of the 21st IEEE-RAS International Conference on Humanoid Robots, 2022

Electromyography-Based, Robust Hand Motion Classification Employing Temporal Multi-Channel Vision Transformers.
Proceedings of the 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2022

2019
Deep Reinforcement Learning Control of an Autonomous Wheeled Robot in a Challenge Task: Combined Visual and Dynamics Sensoring.
Proceedings of the 19th International Conference on Advanced Robotics, 2019


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