Overcoming the challenges of soft robot design with Hexagon student ambassador

Empowering future makers

In manufacturing we often talk about skills shortages, digitalisation and automation—but the interplay between these trends places huge emphasis on digital expertise, innovation and the ability to harness technology to break ground.

Hexagon exists to empower partners in industry to do exactly that. For us, unlocking future capabilities means empowering future makers. The Hexagon student ambassador programme allows the very brightest minds to test, iterate and explore using our tools.

The scheme offers students in universities and educational institutions around the world the chance to experiment in vital fields using Hexagon’s advanced software. Hexagon also provides our student ambassadors mentoring through an international community of experts, direct technical support and access to Hexagon’s e-learning centre.

Analysis of non-linear materials

Philip Ligthart is a Mechanical Engineering master’s student at Stellenbosch University near Cape Town in South Africa. He has a keen interest in optimising the application of non-linear materials to unlock advances in soft robotics.

As part of the Hexagon student ambassador programme, Philip has been using our advanced multiphysics simulation software to design soft robots more efficiently. Here we share how he’s been using Hexagon’s Marc software to optimise the design of soft robots.

Marc is a complete solution that addresses all your nonlinear simulation requirements.

Hexagon student ambassador spotlight

Designing soft robots presents unique challenges for engineers. Soft robots are designed to work alongside humans so they must be durable and operate safely when interacting with people. These robots are often made from hyperelastic materials and feature large deformations. Accurately modelling stress and strain on flexible materials like those used to manufacture soft robots requires advanced non-linear analysis. Softer materials may also be less durable, requiring much more extensive fatigue modelling and analysis during the design process.

This soft robotic finger providing haptic and movement feedback was created by researchers at the Jacobs School of Engineering at UC San Diego.

Chasing that extra 5% of efficiency

Philip Ligthart is a maker with a bright future. He enjoys wrestling with design problems and often finds himself chasing “that extra 5% of efficiency”. Philip approaches the challenges of designing soft robotics using CAE software, which allows him to fine-tune models and reduce the computational expense associated with simulating non-linear materials used in the design process.

As part of Hexagon’s student ambassador programme, Philip recently developed a hierarchical design framework to make the challenging process of designing soft robots more efficient. The framework breaks large problems down into smaller sub-problems, specific to the design, that are simpler or easier to solve. In this framework, each “sub-problem” is treated as a separate design problem. Each sub-problem must have a clearly defined target, plus properties and constraints that are enforced by the designer based on application specifications and availability. For example, a rehabilitation glove can be split into five sub-components, each representing a different finger.

The hierarchical design framework splits large design problems into smaller sub-problems that are faster to solve and require fewer computational resources.

To address the computational challenges of running FE analysis on nonlinear materials, engineers can use reduced-order models to optimise the designs of sub-problems more efficiently within the framework.

By tackling smaller problems first and then assembling them in the full design, engineers can optimise designs using much less computational power. In tests, the design of a soft pneumatic bending actuator using the hierarchical design framework took less than 3% of the time required for a direct design approach. Philip’s programme automatically creates and simulates designs in Marc, an advanced non-linear simulation solution.

Learn more about the hierarchical design framework for soft robots in Philip’s 2023 paper.

Philip’s experience with the Hexagon student ambassador programme

The student ambassador programme provided Philip with the technology and mentorship required to develop his design framework. When asked about his participation in the programme, he said: “It’s been fantastic! Communicating with ambassadors globally has exposed me to a wealth of knowledge. I have learned about others’ work and expertise and gained new skills, including different approaches to using CAE, giving me a fresh perspective.”

In the future, Philip intends to keep using Hexagon’s multiphysics simulation software to solve new problems and create better designs. He intends to pursue a career in research and development and consulting engineering.


This blog was written by Alex Reichanadter, academic programme manager for the design and engineering business unit of Hexagon’s Manufacturing Intelligence division, and Hexagon Student Ambassador Philip Ligthart.



  • Alex Reichanadter

    Alex Reichanadter joined Hexagon in 2021 as a manufacturing solutions integration engineer. Currently, he is the Academic Program Manager for the Design & Engineering business unit. Alex holds a PhD from Purdue University in Chemical Engineering, with an emphasis on cost-effective polymer composites manufacturing. He leverages his work and educational experiences to motivate and empower future engineers with computer aided engineering solutions.

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