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Muhammad Arifin

dblp:246/2574 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 87% Motion planning and robot control · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
robot actuation
0.812024
A Combination of a Controllable Clutch and an Oscillating Slider Crank Mechanism for Ease of Direct-Teaching with Various Payloads · ICRA 2024
Robotics › Robot manipulation › robot programming
robot teaching
0.812024
A Combination of a Controllable Clutch and an Oscillating Slider Crank Mechanism for Ease of Direct-Teaching with Various Payloads · ICRA 2024
Robotics › Motion planning and robot control › robot control
gravity compensation
0.212024
A Combination of a Controllable Clutch and an Oscillating Slider Crank Mechanism for Ease of Direct-Teaching with Various Payloads · ICRA 2024

Methods — techniques the papers use, named apart from their topics

torque control · 0.8passive gravity compensation · 0.8
YearPublicationVenuePosition
2024 A Combination of a Controllable Clutch and an Oscillating Slider Crank Mechanism for Ease of Direct-Teaching with Various Payloads
abstract
Direct teaching is a straightforward way of teaching new motion to robots. Active methods with torque sensors, for example, can be used so that the robot can follow the movements of the human, but such methods introduce delays. Alternatively, series clutch actuators are easily backdrivable without delay. However, vertical joints are subject to gravity torques, which need to be compensated when disengaging the clutch. We implemented passive gravity compensation to counteract the robot’s weight, but this mechanism cannot compensate for varying payloads, as adjustable passive gravity compensation is relatively slow and mechanically complex. The varying payload causes an unintended joint movement, i.e. the arm falls down on its own, which is unacceptable during direct teaching. Therefore, this paper demonstrates how the torque output controlled with series clutch actuators can be used to compensate for varying payloads while maintaining high backdrivability. The proposed method is evaluated on a collaborative robot with a clutch in series for each actuator. Real-world experiments with payloads from 0 to 3 kg are conducted. During the experiments, the operator force is measured to evaluate the proposed method.
Muhammad Arifin, Yuta Kage, Alexander Schmitz, Shigeki Sugano
ICRA1
2018 Ichiro Robots Winning RoboCup 2018 Humanoid TeenSize Soccer Competitions
Muhtadin, Muhammad Reza Arrazi, Sulaiman Ali, Tommy Pratama, Dhany Satrio Wicaksono, Ahmad Hernando Pradanatta Putra, I. Made Pande Ari, Alfi Maulana, Oktaviansyah Purwo Bramastyo, Syifaul Qolby Asshakina, Muhammad Attamimi, Muhammad Arifin, Mauridhi Hery Purnomo, Djoko Purwanto
RoboCup12