J.M.P. Geraedts
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17 records found
1
The computational design of knitting attracted increased attention in recent years. In this dissertation, we consider the customized design and fabrication of 3D and 4D garments as knitwears. The 3D knitwear fits the target human body, and the 4D knitwear also considers comfort during body movement. The main research question (RQ) is: How to design customized 3D and 4D knitwear and generate instructions for a digital knitting machine?
In this dissertation, we researched computational knitwear design methods. We considered not only 3D fitting but also comfort during motion (4D). Our research can be applied in garment production (especially mass customization) or other knitting applications. Garment designers and other industrial designers can use the proposed methods to generate knitting instructions for free-form 3D surfaces. Our 4D design method helps designers place elastic or other varied knitting structures while keeping the intended 3D shape. This dissertation presents new perspectives on computational approaches to existing manufacturing techniques. It also provides enough details to further develop such design systems to be applied in practice. ...
The computational design of knitting attracted increased attention in recent years. In this dissertation, we consider the customized design and fabrication of 3D and 4D garments as knitwears. The 3D knitwear fits the target human body, and the 4D knitwear also considers comfort during body movement. The main research question (RQ) is: How to design customized 3D and 4D knitwear and generate instructions for a digital knitting machine?
In this dissertation, we researched computational knitwear design methods. We considered not only 3D fitting but also comfort during motion (4D). Our research can be applied in garment production (especially mass customization) or other knitting applications. Garment designers and other industrial designers can use the proposed methods to generate knitting instructions for free-form 3D surfaces. Our 4D design method helps designers place elastic or other varied knitting structures while keeping the intended 3D shape. This dissertation presents new perspectives on computational approaches to existing manufacturing techniques. It also provides enough details to further develop such design systems to be applied in practice.
Kinematics Computing for Soft Robots
Method based on Geometric Computing and Machine Learning
In model-based robot control, kinematics comprise the fundamental knowledge that can be used to build the mathematical connection between control parameters and robot status. Unlike rigid robots, whose kinematics are well studied and have fast (analytical) solutions, effective and general kinematics computing methods for soft robot systems are still lacking. According to the modeling perspective (i.e., forward kinematics (FK)), predicting the whole-body shape of soft robots under actuation is a non-trivial task since the non-linear deformation in robot bodies and the hyperplastic properties of soft materials create challenges in balancing accuracy and computational costs in existing FK models. The lack of modeling tools further brings the difficulties in developing advanced algorithms to inverse kinematics (IK) and (statics) control thereafter. This Ph.D. project aims to develop a general soft robot kinematics computing pipeline, that can contribute to the effective control of soft robot systems to accomplish given tasks.
A fast numerical simulator for soft robots is firstly presented in this thesis, in which the shape of the robot body is discretely represented by volumetric elements. The development of this simulator was inspired by the fact that the hard-to-model actuation input (e.g., cable force, pressure, and electronic field) in soft robot systems can be directly modeled or transformed to fit the shape change in actuation elements. An optimization pipeline was built to minimize elastic energy in the body elements and compute the deformed shape with actuation parameters as input. As a general numerical simulator, it supports the modeling of various types of actuation, and the hyperelastic soft material properties are integrated. A fast collision checking and response model was added to predict the behavior of soft robots under robot-robot collisions and robot-environment interactions. The numerical computing process of our simulator shows good convergence, even for soft robots with large (rotational) deformation in their bodies, and can therefore balance the computational cost and model precision. In comparison to commercial \textit{finite element analysis} (FEA) software, this geometry-based simulator demonstrates a 20-fold faster computing speed, and the simulation result can well fit the shape that was captured from the physical setup.
The IK problem of soft robots is defined as computing proper actuation parameters that drive soft robots to accomplish given tasks. In this thesis, task-specific IK objectives (which are mainly geometrically defined) are formulated, and the optimal actuation parameters are detected using gradient-based iteration. Through the developed simulator, the gradients of objective functions are estimated using numerical differences. The sequence of motion can be successfully computed using this IK solver, and its efficiency has been verified in two case studies, which include path-following and object pick-and-place.
For the final stage of this Ph.D. project, the speed and precision of the IK solver are enhanced through machine learning. Fully connected neural networks are invited to fit functions of FK and the Jacobian of IK-related objectives. With the high efficiency in the forward propagation of networks (in analytical form), the gradient-based IK solver can run in real-time. Sim-to-real transfer learning is applied to eliminate the reality gap and make the computed actuation parameters more precise in physical setups. Applying sim-to-real transfer learning can also benefit the efficiency of the data generation process. In our pipeline, massive training data is first generated in a virtual environment using a fast simulator; thereafter, a lightweight network layer is employed to map the result of the simulation to the physical hardware. As a result, the amount of physical data can be reduced by 60% to train a network that accurately computes IK solutions.
In conclusion, this dissertation presents a pipeline that computes kinematics solutions for soft robots. A fast geometry-based simulator is presented to contribute to building an iteration-based numerical IK solver. Machine learning is applied to accelerate IK computing to real-time speed with enhanced precision. Task-specific kinematics control is realized in different soft robot systems to verify the effectiveness of the proposed method. The algorithms and code presented in this Ph.D. thesis are open-sourced for researchers and designers, and have the potential to become a general tool for designing and controlling soft robots. Future studies on the design optimization and high-level control of soft robots can all benefit from the research outcomes of this project. ...
In model-based robot control, kinematics comprise the fundamental knowledge that can be used to build the mathematical connection between control parameters and robot status. Unlike rigid robots, whose kinematics are well studied and have fast (analytical) solutions, effective and general kinematics computing methods for soft robot systems are still lacking. According to the modeling perspective (i.e., forward kinematics (FK)), predicting the whole-body shape of soft robots under actuation is a non-trivial task since the non-linear deformation in robot bodies and the hyperplastic properties of soft materials create challenges in balancing accuracy and computational costs in existing FK models. The lack of modeling tools further brings the difficulties in developing advanced algorithms to inverse kinematics (IK) and (statics) control thereafter. This Ph.D. project aims to develop a general soft robot kinematics computing pipeline, that can contribute to the effective control of soft robot systems to accomplish given tasks.
A fast numerical simulator for soft robots is firstly presented in this thesis, in which the shape of the robot body is discretely represented by volumetric elements. The development of this simulator was inspired by the fact that the hard-to-model actuation input (e.g., cable force, pressure, and electronic field) in soft robot systems can be directly modeled or transformed to fit the shape change in actuation elements. An optimization pipeline was built to minimize elastic energy in the body elements and compute the deformed shape with actuation parameters as input. As a general numerical simulator, it supports the modeling of various types of actuation, and the hyperelastic soft material properties are integrated. A fast collision checking and response model was added to predict the behavior of soft robots under robot-robot collisions and robot-environment interactions. The numerical computing process of our simulator shows good convergence, even for soft robots with large (rotational) deformation in their bodies, and can therefore balance the computational cost and model precision. In comparison to commercial \textit{finite element analysis} (FEA) software, this geometry-based simulator demonstrates a 20-fold faster computing speed, and the simulation result can well fit the shape that was captured from the physical setup.
The IK problem of soft robots is defined as computing proper actuation parameters that drive soft robots to accomplish given tasks. In this thesis, task-specific IK objectives (which are mainly geometrically defined) are formulated, and the optimal actuation parameters are detected using gradient-based iteration. Through the developed simulator, the gradients of objective functions are estimated using numerical differences. The sequence of motion can be successfully computed using this IK solver, and its efficiency has been verified in two case studies, which include path-following and object pick-and-place.
For the final stage of this Ph.D. project, the speed and precision of the IK solver are enhanced through machine learning. Fully connected neural networks are invited to fit functions of FK and the Jacobian of IK-related objectives. With the high efficiency in the forward propagation of networks (in analytical form), the gradient-based IK solver can run in real-time. Sim-to-real transfer learning is applied to eliminate the reality gap and make the computed actuation parameters more precise in physical setups. Applying sim-to-real transfer learning can also benefit the efficiency of the data generation process. In our pipeline, massive training data is first generated in a virtual environment using a fast simulator; thereafter, a lightweight network layer is employed to map the result of the simulation to the physical hardware. As a result, the amount of physical data can be reduced by 60% to train a network that accurately computes IK solutions.
In conclusion, this dissertation presents a pipeline that computes kinematics solutions for soft robots. A fast geometry-based simulator is presented to contribute to building an iteration-based numerical IK solver. Machine learning is applied to accelerate IK computing to real-time speed with enhanced precision. Task-specific kinematics control is realized in different soft robot systems to verify the effectiveness of the proposed method. The algorithms and code presented in this Ph.D. thesis are open-sourced for researchers and designers, and have the potential to become a general tool for designing and controlling soft robots. Future studies on the design optimization and high-level control of soft robots can all benefit from the research outcomes of this project.
Transcended Manufacturing
The mass-production of one-of-a-kind products
From Trash to Treasure
Design of a gripper for automated sorting of mixed aluminium scrap to create added value
Investigation of the Effect of the Green Glaze Layer in the Background of Girl with a Pearl Earring by Johannes Vermeer
An Approach using Optical Properties of Paints and Rendering Technique
Fused Deposition Modelling in Industry 4.0
Extend the capabilities of fused deposition modelling to industry 4.0 standard
This is not a painting
Scanning and printing a painting's appearance
Hands can
Determining the location and range of motion of digital joints in 3D scans
The aim of this research is to develop a method that reliably and reproducability determine the range of motion of the digits. In current practice, the angles are measured using a goniometer. This method is very imprecise. Three methods to determine the location of joints in 3D hand scans can be distinguished: using heuristics, computer vision, and deep learning. Of those, deep learning is the most flexible, modern and accurate method and is therefore applied. The end result is a matrix containing the range of motion per joint and is applied to anatomically correctly manipulate a 3D model. For ease of manipulation, a physical manipulator is proposed. The results of this novel method show lower interrater differences than measurements with a goniometer. ...
The aim of this research is to develop a method that reliably and reproducability determine the range of motion of the digits. In current practice, the angles are measured using a goniometer. This method is very imprecise. Three methods to determine the location of joints in 3D hand scans can be distinguished: using heuristics, computer vision, and deep learning. Of those, deep learning is the most flexible, modern and accurate method and is therefore applied. The end result is a matrix containing the range of motion per joint and is applied to anatomically correctly manipulate a 3D model. For ease of manipulation, a physical manipulator is proposed. The results of this novel method show lower interrater differences than measurements with a goniometer.
Comfort -
As a first step the research focussed on how the users could benefit best from such a smart system. A force analysis validated the severity of the complaints and user interviews highlighted that users can develop a fear for mobility. The smart system should comfort the user by taking away this fear and it should comfort the push attendant by lowering the use force.
Support -
Some types of power assisted mobility aids have a high number of accidents. This shows that the user group is vulnerable. An analysis was done to test whether the Rollz Motion would be safe enough to motorise. Assistive supportive technology needs to be implemented in the design of the drive system to generate the necessary safety.
Perception -
Mobility aids suffer from product related stigma. This creates a threshold of going for a walk, makes users insecure and can have a negative effect on the mobility of the user. For new product development the stigma needs to be redesigned to make users proud and confident about using their product.
Prototype -
The first version of a push supportive system has been designed and prototyped. This system utilises a motor control algorithm that proved to be able to provide robust output in different contexts. It showed potential to lower the force of pushing a person in the Rollz Motion on a hill from 200N to 10N. ...
Comfort -
As a first step the research focussed on how the users could benefit best from such a smart system. A force analysis validated the severity of the complaints and user interviews highlighted that users can develop a fear for mobility. The smart system should comfort the user by taking away this fear and it should comfort the push attendant by lowering the use force.
Support -
Some types of power assisted mobility aids have a high number of accidents. This shows that the user group is vulnerable. An analysis was done to test whether the Rollz Motion would be safe enough to motorise. Assistive supportive technology needs to be implemented in the design of the drive system to generate the necessary safety.
Perception -
Mobility aids suffer from product related stigma. This creates a threshold of going for a walk, makes users insecure and can have a negative effect on the mobility of the user. For new product development the stigma needs to be redesigned to make users proud and confident about using their product.
Prototype -
The first version of a push supportive system has been designed and prototyped. This system utilises a motor control algorithm that proved to be able to provide robust output in different contexts. It showed potential to lower the force of pushing a person in the Rollz Motion on a hill from 200N to 10N.
Development of a high resolution topography and colour scannner
Applied to the craquelure pattern of paintings
3D-Paintbrush
Melting and cooling plastics
Design for Recycling of Electronic Products
How to bridge the gap between design methods and recycling practices
Design is seen as pivotal in the creation of products that can facilitate the recycling process. For this reason, in the past two decades there has been considerable research on DfR, resulting in a large number of methods and tools being developed. The aim of these methods is to assist designers in assessing the recyclability of their designs and to select adequate product design features that facilitate the recycling process. However, these methods do not seem to have been very effective; particularly not in the case of electronic products. This is because, despite the considerable number of methods developed thus far, and what they claim in theory, electronic products are still not being optimally disintegrated and separated in actual recycling processes. Consequently, the aim of this thesis is to uncover the various reasons for the mismatch between the theory and practice of DfR by undertaking a number of studies. ...
Design is seen as pivotal in the creation of products that can facilitate the recycling process. For this reason, in the past two decades there has been considerable research on DfR, resulting in a large number of methods and tools being developed. The aim of these methods is to assist designers in assessing the recyclability of their designs and to select adequate product design features that facilitate the recycling process. However, these methods do not seem to have been very effective; particularly not in the case of electronic products. This is because, despite the considerable number of methods developed thus far, and what they claim in theory, electronic products are still not being optimally disintegrated and separated in actual recycling processes. Consequently, the aim of this thesis is to uncover the various reasons for the mismatch between the theory and practice of DfR by undertaking a number of studies.
3D paint brush
A journey of plastic
An extruder is a pipe (barrel) with a screw inside it and heating elements around it (figure 3). When the screw is rotated the threads (grooved ridges) will push the plastic forwards. The heating elements will melt the plastic along the way. The plastic will enter the extruder in a solid state and will leave the extruder in a molten state.
By manually controlling the extruder the designer can express her artistic creativity in 3D. The context for the artwork of Tiwánee van der Horst will be urban residential areas. In these areas she will integrate her artwork into existing features of buildings. The extruder will be used as a 3D paint brush in such a urban residential area.
The storyline throughout this report will be a journey of plastic. In the report it will be explained how plastic granulate (small pieces of plastic 4 x 4 x 4mm) is transformed and controlled by the 3D paint brush into plastic artworks.
...
An extruder is a pipe (barrel) with a screw inside it and heating elements around it (figure 3). When the screw is rotated the threads (grooved ridges) will push the plastic forwards. The heating elements will melt the plastic along the way. The plastic will enter the extruder in a solid state and will leave the extruder in a molten state.
By manually controlling the extruder the designer can express her artistic creativity in 3D. The context for the artwork of Tiwánee van der Horst will be urban residential areas. In these areas she will integrate her artwork into existing features of buildings. The extruder will be used as a 3D paint brush in such a urban residential area.
The storyline throughout this report will be a journey of plastic. In the report it will be explained how plastic granulate (small pieces of plastic 4 x 4 x 4mm) is transformed and controlled by the 3D paint brush into plastic artworks.
Design for the railway worker
Relieving the physical load on railway workers
Combining 3D Hand Scanning and Medical Thermography
Exploring Technology and Applications
Combining 3D hand scanning with medical thermography creates opportunities for product designers and medical professionals to better help people with hand conditions such as, among others, rheumatoid arthritis, diabetes and Raynaud’s syndrome.
This thesis explores potential applications and technology needed to combine both modalities, by presenting the development of a thermal camera module and its integration into the existing scanner workflow. Research conducted and results obtained show promise and provide a foundation for further research into this multi-modal system’s possibilities, limits and best suitable applications. ...
Combining 3D hand scanning with medical thermography creates opportunities for product designers and medical professionals to better help people with hand conditions such as, among others, rheumatoid arthritis, diabetes and Raynaud’s syndrome.
This thesis explores potential applications and technology needed to combine both modalities, by presenting the development of a thermal camera module and its integration into the existing scanner workflow. Research conducted and results obtained show promise and provide a foundation for further research into this multi-modal system’s possibilities, limits and best suitable applications.
Design Methodology for Additive Manufacturing
Supporting Designers in the Exploitation of Additive Manufacturing Affordances