Contact Detection and Manipulation With a Shape-Memory Alloy Based Soft Gripper

Soft robotics offers the opportunity to create dexterous machines that can safely handle delicate objects. Grippers made from deformable actuators and compliant materials can deform around the objects with which they come in contact. The continuum mechanics of flexible manipulators can be leveraged for safe manipulation tasks such as twisting and grasping during manufacturing. However, to achieve this goal, contact sensing and controls for manipulators in these soft systems still remain a challenge in the field. This paper demonstrates a shape-memory alloy actuated soft gripper, with each finger able to bend about multiple axes. This enables the soft gripper to perform twisting tasks and handle various and fragile objects. Using capacitive bend sensors, we also demonstrate that the measured impedance of motion can be used as a proxy for contact, greatly increasing performance in a delicate manipulation task

Authors

Institutions

Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-06-06
DOI
https://doi.org/10.1109/lra.2025.3577465
Citations
1
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Contact Detection and Manipulation With a Shape-Memory Alloy Based Soft Gripper

Dinesh K. Patel, Carmel Majidi, Philip R. LeDuc, Richard Desatnik et al.
1 citations
IEEE Robotics and Automation Letters
Soft Robotics and Applications
0.67
article

Contact Detection and Manipulation With a Shape-Memory Alloy Based Soft Gripper

Dinesh K. Patel, Carmel Majidi, Philip R. LeDuc, Richard Desatnik, Louis Plottel
article en
1 citations

Abstract

Soft robotics offers the opportunity to create dexterous machines that can safely handle delicate objects. Grippers made from deformable actuators and compliant materials can deform around the objects with which they come in contact. The continuum mechanics of flexible manipulators can be leveraged for safe manipulation tasks such as twisting and grasping during manufacturing. However, to achieve this goal, contact sensing and controls for manipulators in these soft systems still remain a challenge in the field. This paper demonstrates a shape-memory alloy actuated soft gripper, with each finger able to bend about multiple axes. This enables the soft gripper to perform twisting tasks and handle various and fragile objects. Using capacitive bend sensors, we also demonstrate that the measured impedance of motion can be used as a proxy for contact, greatly increasing performance in a delicate manipulation task

IEEE Robotics and Automation LettersVol. 10(7)
Carnegie Mellon University (US)
National Science Foundation
Openalex Percentile: Top 31%
Soft Robotics and Applications
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.