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Jungwook Mun

2 accepted papers

2024

Impact of Physical Parameters and Vision Data on Deep Learning-Based Grip Force Estimation for Fluidic Origami Soft Grippers

RA-L 2024

Knowing the gripping force being applied to an object is important for improving the quality of the grip, as well as preventing surface damage or breakage of fragile objects. In the case of soft grippers, however, an attaching or embedding of force/pressure sensors can compromise their adaptability

Cited by 4SourceScholar
2023

HybGrasp: A Hybrid Learning-to-Adapt Architecture for Efficient Robot Grasping

RA-L 2023

Despite the prevalence of robotic manipulation tasks in various real-world applications of different requirements and needs, there has been a lack of focus on enhancing the adaptability of robotic grasping systems. Most of the current literature constructs models around a single gripper, succumbing

Cited by 4SourceScholar