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Stein Crispel

dblp:251/4812 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0001-6225-1532ORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 1 since 2021Systems, architecture and hardware · 2 · 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 · 100%
Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
robot actuation
0.612022
R2poweR: The Proof-of-Concept of a Backdrivable, High-Ratio Gearbox for Human-Robot Collaboration · ICRA 2022
Human-robot interaction › physical human-robot interaction
physical human-robot collaboration
0.212022
R2poweR: The Proof-of-Concept of a Backdrivable, High-Ratio Gearbox for Human-Robot Collaboration · ICRA 2022

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

prototype testing · 1.1proof-of-concept prototyping · 1.1
YearPublicationVenuePosition
2022 R2poweR: The Proof-of-Concept of a Backdrivable, High-Ratio Gearbox for Human-Robot Collaboration
abstract
Robotic engineers face major challenges to solve the complex actuation needs of Human-Robot Collaboration with existing act robotic gearboxes. Available technologies comprise high-ratio Planetary Gearheads, Cycloid Drives and Harmonic Drives, inherited from conventional industrial robotics. Alternative approaches include Direct-Drive and Quasi Direct-Drive actuation strategies, which propose to cancel or substantially reduce gear ratio, in order to minimize reflected inertia and attain enough backdrivability for collaborative tasks. This paper presents the proof-of-concept validation of a novel high-ratio, Wolfrom-based, gearbox technology that follows a different approach to attain the same objective. Testing five different gearbox prototypes, we confirm the ability of the R2poweR technology to improve efficiency and backdrivability while retaining the weight and control advantages derived from the use of high reduction ratios. The result is a highly efficient, backdrivable, high-ratio gearbox with exciting Huma-Robot Collaboration potential.
Pablo López-García, Stein Crispel, A. Varadharajan, Elias Saerens, Tom Verstraten, Bram Vanderborght, Dirk Lefeber
ICRA2
2020 Scaling laws for parallel motor-gearbox arrangements
abstract
Research towards (compliant) actuators, especially redundant ones like the Series Parallel Elastic Actuator (SPEA), has led to the development of drive trains, which have demonstrated to increase efficiency, torque-to-mass-ratio, power-to-mass ratio, etc. In the field of robotics such drive trains can be implemented, enabling technological improvements like safe, adaptable and energy-efficient robots. The choice of the used motor and transmission system, as well as the compliant elements composing the drive train, are highly dependent of the application and more specifically on the allowable weight and size. In order to optimally design an actuator adapted to the desired characteristics and the available space, scaling laws governing the specific actuator can simplify and enhance the reliability of the design process. Although scaling laws of electric motors and links are known, none have been investigated for a complete redundant drive train. The present study proposes to fill this gap by providing scaling laws for electric motors in combination with their transmission system. These laws are extended towards parallelization, i.e. replacing one big motor with gearbox by several smaller ones in parallel. The results of this study show that the torque/mass ratio for a motor-gearbox can not be increased by parallelization, but that it can increase the torque/volume ratio. This is however only the case if a good topology is chosen.
Elias Saerens, Stein Crispel, Pablo López-García, Vincent Ducastel, Jarl Beckers, Joris De Winter, Raphael Furnemont, Bram Vanderborght, Tom Verstraten, Dirk Lefeber
IROS2