ToRoS: A Topology Optimization Approach for Designing Robotic Skins
DescriptionSoft robotics offers unique advantages in manipulating fragile or deformable
objects, human-robot interaction, and exploring inaccessible terrain. How-
ever, designing soft robots that produce large, targeted deformations is
challenging. In this paper, we propose a new methodology for designing
soft robots that combines optimization-based design with a simple and
cost-efficient manufacturing process. Our approach is centered around the
concept of robotic skins—thin fabrics with 3D-printed reinforcement pat-
terns that augment and control plain silicone actuators. By decoupling shape
control and actuation, our approach enables a simpler and cost-efficient man-
ufacturing process. Unlike previous methods that rely on empirical design
heuristics for generating desired deformations, our approach automatically
discovers complex reinforcement patterns without any need for domain
knowledge or human intervention. This is achieved by casting reinforce-
ment design as a nonlinear constrained optimization problem and using
a novel, three-field topology optimization approach tailored fabrics with
3D-printed reinforcements. We demonstrate the potential of our approach by
designing soft robotic actuators capable of various motions, such as bending,
contraction, twist, and combinations thereof. We also demonstrate applica-
tions of our robotic skins to robotic grasping with a soft three-finger gripper
and locomotion tasks for a soft quadrupedal robot.
objects, human-robot interaction, and exploring inaccessible terrain. How-
ever, designing soft robots that produce large, targeted deformations is
challenging. In this paper, we propose a new methodology for designing
soft robots that combines optimization-based design with a simple and
cost-efficient manufacturing process. Our approach is centered around the
concept of robotic skins—thin fabrics with 3D-printed reinforcement pat-
terns that augment and control plain silicone actuators. By decoupling shape
control and actuation, our approach enables a simpler and cost-efficient man-
ufacturing process. Unlike previous methods that rely on empirical design
heuristics for generating desired deformations, our approach automatically
discovers complex reinforcement patterns without any need for domain
knowledge or human intervention. This is achieved by casting reinforce-
ment design as a nonlinear constrained optimization problem and using
a novel, three-field topology optimization approach tailored fabrics with
3D-printed reinforcements. We demonstrate the potential of our approach by
designing soft robotic actuators capable of various motions, such as bending,
contraction, twist, and combinations thereof. We also demonstrate applica-
tions of our robotic skins to robotic grasping with a soft three-finger gripper
and locomotion tasks for a soft quadrupedal robot.
Event Type
Technical Papers
TimeTuesday, 12 December 20239:30am - 12:45pm
LocationDarling Harbour Theatre, Level 2 (Convention Centre)
