Tito Pradhono Tomo — 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 ↗

2022

A Robotic Grasping State Perception Framework With Multi-Phase Tactile Information and Ensemble Learning

Gang Yan, Alexander Schmitz, Satoshi Funabashi, Sophon Somlor, Tito Pradhono Tomo, Shigeki Sugano

RA-L 2022

Recently, tactile sensing has attracted increasing attention for robotic manipulation. Predicting the grasping stability before lifting objects and detecting the ongoing/onset of slip after lifting objects are two critical and widely studied tasks in robotic tactile manipulation. Previous methods fo

Cited by 20 Source ↗Scholar ↗

2022

Detection of Slip from Vision and Touch

Gang Yan, Alexander Schmitz, Tito Pradhono Tomo, Sophon Somlor, Satoshi Funabashi, Shigeki Sugano

ICRA 2022poster

Detecting the onset/ongoing of slip, i.e. if a grasped object is slipping or will slip from the gripper while being lifted, is crucial. Conventionally, it is regarded as a tactile sensing related problem. However, recently multi-modal robotic learning has become popular and is expected to boost the…

Cited by 25 Source ↗Scholar ↗

2021

"Safe Skin" - A Low-Cost Capacitive Proximity-Force-Fusion Sensor for Safety in Robots

Zhen Wang, Heyang Gao, Alexander Schmitz, Sophon Somlor, Tito Pradhono Tomo, Shigeki Sugano

IROS 2021poster

This paper presents the design and evaluation of the low-cost capacitive proximity-force-fusion sensor "safe skin", which can measure simultaneously the proximity of humans as well as the contact force. It was designed such that the force and proximity sensing functions can work concurrently without…

Cited by 6 Source ↗Scholar ↗

2021

SCT-CNN: A Spatio-Channel-Temporal Attention CNN for Grasp Stability Prediction

Gang Yan, Alexander Schmitz, Satoshi Funabashi, Sophon Somlor, Tito Pradhono Tomo, Shigeki Sugano

ICRA 2021poster

Recently, tactile sensing has attracted great interest for robotic manipulation. Predicting if a grasp will be stable or not, i.e. if the grasped object will drop out of the gripper while being lifted, can aid robust robotic grasping. Previous methods paid equal attention to all regions of the tacti…

Cited by 27 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 ↗

2020

Stable In-Grasp Manipulation with a Low-Cost Robot Hand by Using 3-Axis Tactile Sensors with a CNN

Satoshi Funabashi, Tomoki Isobe, Shun Ogasa, Tetsuya Ogata, Alexander Schmitz, Tito Pradhono Tomo +1

IROS 2020poster

The use of tactile information is one of the most important factors for achieving stable in-grasp manipulation. Especially with low-cost robotic hands that provide low-precision control, robust in-grasp manipulation is challenging. Abundant tactile information could provide the required feed-back to…

Cited by 23 Source ↗Scholar ↗

2020

Variable In-Hand Manipulations for Tactile-Driven Robot Hand via CNN-LSTM

Satoshi Funabashi, Shun Ogasa, Tomoki Isobe, Tetsuya Ogata, Alexander Schmitz, Tito Pradhono Tomo +1

IROS 2020poster

Performing various in-hand manipulation tasks, without learning each individual task, would enable robots to act more versatile, while reducing the effort for training. However, in general it is difficult to achieve stable in-hand manipulation, because the contact state between the fingertips become…

Cited by 16 Source ↗Scholar ↗

2019

Sequential clustering for tactile image compression to enable direct adaptive feedback

Andreas Geier, Gang Yan, Tito Pradhono Tomo, Shun Ogasa, Sophon Somlor, Alexander Schmitz +1

IROS 2019poster

The sense of touch is often crucial for humans to perform manipulation tasks. Providing tactile feedback during teleoperation or for users of prosthetic devices would be beneficial. However, the representation of tactile information constitutes a major technical challenge, since the numerous and pos…

Cited by 1 Source ↗Scholar ↗

2018

A New Silicone Structure for uSkin - A Soft, Distributed, Digital 3-Axis Skin Sensor and Its Integration on the Humanoid Robot iCub

Tito Pradhono Tomo, Massimo Regoli, Alexander Schmitz, Lorenzo Natale, Harris Kristanto, Sophon Somlor +3

RA-L 2018

Tactile sensing is one important element that can enable robots to interact with an unstructured world. By having tactile perception, a robot can explore its environment by touching objects. Like human skin, a tactile sensor that can provide rich information such as distributed normal and shear forc

Cited by 132 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 ↗

2018

An Adjustable Force Sensitive Sensor with an Electromagnet for a Soft, Distributed, Digital 3-axis Skin Sensor

Alexis C. Holgado, Javier A. Alvarez Lopez, Alexander Schmitz, Tito Pradhono Tomo, Sophon Somlor, Lorenzo Jamone +1

IROS 2018poster

Typically, the range and sensitivity of force sensors are determined during production. However, to be able to do both delicate and high-force demanding work, adjustable force sensitivity would be beneficial. The current paper proposes such a sensor by implementing a planar electromagnet above a 3-a…

Cited by 11 Source ↗Scholar ↗

2018

Covering a Robot Fingertip With uSkin: A Soft Electronic Skin With Distributed 3-Axis Force Sensitive Elements for Robot Hands

Tito Pradhono Tomo, Alexander Schmitz, Wai Keat Wong, Harris Kristanto, Sophon Somlor, Jinsun Hwang +2

RA-L 2018

Distributed tactile sensing is crucial to perform stable, subtle, and precise manipulation so that a robot can recognize and handle objects properly. However, currently existing skin sensors still have common problems such as complex and expensive production or are difficult to integrate into robot

Cited by 150 Source ↗Scholar ↗