Prathamesh Sathe — accepted AI-conference papers

2023

FingerTac - An Interchangeable and Wearable Tactile Sensor for the Fingertips of Human and Robot Hands

Prathamesh Sathe, Alexander Schmitz, Tito Pradhono Tomo, Sophon Somlor, Satoshi Funabashi, Sugano Shigeki

IROS 2023poster

Skill transfer from humans to robots is challenging. Presently, many researchers focus on capturing only position or joint angle data from humans to teach the robots. Even though this approach has yielded impressive results for grasping applications, reconstructing motion for object handling or fine…

Cited by 1 Source ↗Scholar ↗

2020

Development of Exo-Glove for Measuring 3-axis Forces Acting on the Human Finger without Obstructing Natural Human-Object Interaction

Prathamesh Sathe, Alexander Schmitz, Harris Kristanto, Chincheng Hsu, Tito Pradhono Tomo, Sophon Somlor +1

IROS 2020poster

Measuring the forces that humans exert with their fingers could have many potential applications, such as skill transfer from human experts to robots or monitoring humans. In this paper we introduce the "Exo-Glove" system, which can measure the joint angles and forces acting on the human finger with…

Cited by 4 Source ↗Scholar ↗

2018

A Wearable Three-Axis Tactile Sensor for Human Fingertips

Harris Kristanto, Prathamesh Sathe, Alexander Schmitz, Tito Pradhono Tomo, Sophon Somlor, Shigeki Sugano

RA-L 2018

Human training data can scaffold robot imitation learning. However, most datagloves only record joint angles, but for many tasks, force control is more important. They also cover the human skin, thereby making a natural interaction of the human with the object impossible. This letter suggests a wear

Cited by 17 Source ↗Scholar ↗