The SLS-generated Soft Robotic Hand
The SLS-generated Soft Robotic Hand
An Integrated Approach using Additive Manufacturing and Reinforcement Learning

To develop
a robotic system for a complex task
is a time- consuming process. Merging
methods available today, a new ap- proach for a faster realization of a multi-finger soft robotic hand is presented here. This
paper introduces a robotic hand with four fingers and 12 Degrees of Freedom
(DoFs) using bellow actuators. The hand is generated via Selective
Laser Sintering (SLS), an Additive Manufacturing method. The complex task execution of a specific action,
i.e. the lifting, rotating and precise positioning of a handling- object with this robotic hand, is used to structure
the whole develop- ment process. To
validate reliable functionality of the hand from the beginning, each development
stage is SLS-generated and the targeted task execution is trained
via Reinforcement Learning, a machine learning approach.
Optimization points are subsequently derived
and fed back into the hardware development. With this Concurrent
Engineering strategy a fast development of this robotic
hand is possible. The paper
outlines the relevant key strategies and gives insight into
the design process. At the end, the
final hand with its capabilities is presented and discussed.

Document type:
Special publication
Title Version
The SLS-generated Soft Robotic Hand
The SLS-generated Soft Robotic Hand