An Open Source Design Optimization Toolbox Evaluated on a Soft Finger
Author:
Affiliation:
1. Institute for Engineering Sciences, O'Higgins University, O'Higgins, Chile
2. Team DEFROST at Inria Lille - Nord Europe as well as CRIStAL, University of Lille, Lille, France
Funder
Agencia Nacional de Investigación y Desarrollo
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/7083369/10185095/10202189.pdf?arnumber=10202189
Reference19 articles.
1. Co-Learning of Task and Sensor Placement for Soft Robotics
2. MakeSense: Automated Sensor Design for Proprioceptive Soft Robots
3. A Model-Based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics
4. Software toolkit for modeling, simulation, and control of soft robots
5. Soft robot co-design benchmark for locomotion in diverse environments;wang,2023
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1. Towards Bespoke Soft Grippers through Voxel-Scale Metamaterial Topology Optimisation;2024 IEEE 7th International Conference on Soft Robotics (RoboSoft);2024-04-14
2. Design Optimization of a Soft Gripper Using Self-Contacts;2024 IEEE 7th International Conference on Soft Robotics (RoboSoft);2024-04-14
3. Diversity‐Based Topology Optimization of Soft Robotic Grippers;Advanced Intelligent Systems;2024-01-18
4. Educational Resources for Robotics: Accessible Lectures and Toolboxes;Mechanisms and Machine Science;2024
5. Automated design of 4D-printed soft robots;Smart Materials in Additive Manufacturing, Volume 3;2024
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