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This book explains how to design and control a soft robot in understandable language. In addition, it provides a comprehensive coverage of the essential theory and techniques used in soft robotics that can be used by graduate students in soft robotics. The book covers several key areas in soft robots, ranging from design and fabrication to modelling and control. It also includes many case studies and examples. The book clearly explains mathematical concepts and uses illustrative explanation to help engineers and junior graduate students understand the physical meaning of the key concepts and approaches in soft robotics. Reading this book gives professional engineers and students a sound knowledge of soft robotics that they can take to their careers and research.

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Citations: 2

Journal article

Nanayakkara T, 2024,

Introduction

, Handbook on Soft Robotics, Pages: 1-12

Softness has a meaning relative to the forces and their frequencies an object experiences.

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Book chapter

Nanayakkara T, Mulvey B, Perera S, Ge Y, Yu Z, Sunilkumar Pet al., 2024,

Soft robots as a platform to understand embodied intelligence

, Handbook on Soft Robotics, Pages: 35-84

This chapter addresses some of the possible missing pieces to understand the gulf between robots and biological beings in negotiating movements in a natural world. More specifically, we discuss the overarching question of understanding how passive dynamics and computing can come together to solve complex interaction problems. The elegance of physical interactions we have in daily life appears to come from a fine interplay among the dynamics and computing in the brain, the body, and the environment. However, it is difficult to map this out using human participants alone. Can we use robots as a proxy to living beings to understand the nuances of such interactions since we can control and measure details of information flow? We will group examples under three phenomena we believe are important to untangle the puzzle: Ghost circuits, kinematic tuning, and behavioral lensing on which we will elaborate further in this chapter.

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Citations: 2

Journal article

Spyrakos-Papastavridis E, Childs PRN, Dai JS, 2024,

Confutation of the “Counterexample to passivity preservation for variable impedance control of compliant robots”

, IEEE-ASME Transactions on Mechatronics, Vol: 29, Pages: 4023-4032, ISSN: 1083-4435

This letter reveals the incorrect argumentation, erroneous mathematical calculations, and misleading observations reported in the article titled “Counterexample to Passivity Preservation for Variable Impedance Control of Compliant Robots” published in volume 28, issue 1 of this journal, in February 2023. All the calculations in the said article are either incorrect or redundant, and this letter apodictically reveals that the peculiar simulation results therein contained were produced from a failure to follow the implementation guidelines delineated in the original publication. This letter further generates a set of examples to confute the so-called “counterexamples,” thereby proving the erroneousness of the article's argumentation. Furthermore, numerous of the incorrect claims contained in the said article stand in stark opposition to results and theories reported in the robotics literature over the last three decades. This letter provides point-to-point refutations of the erroneous comments and calculations contained in all five pages of the article titled “Counterexample to Passivity Preservation for Variable Impedance Control of Compliant Robots” (Medrano-Cerda, 2023), thereby invalidating all its arguments and exposing its want of substantiality to the reader.

Journal article

Anza-Ramirez C, Cardenas MK, Landeiro F, Montesinos R, Custodio N, Da Re M, Calvo RA, Belon-Hercilla V, Cuba MS, Bernabe A, Butler C, Miranda J, IMPACT Dementia Study Groupet al., 2024,

Public Health.

, Alzheimers Dement, Vol: 20 Suppl 7

BACKGROUND: Dementia is a global health challenge, especially in low- and middle-income countries like Peru, where diagnosis, access, and awareness are limited. Within the IMPACT Dementia project, a component focuses on developing, testing, and implementing an mHealth-enabled system for dementia screening and diagnosis, and assessing its cost-effectiveness. METHODS: Phase I. To develop a dementia diagnostic screening mHealth system: The features of the screening tool will be locally adapted using a co-design approach including community members and community health workers (CHW) in four regions in Peru (Lima, Tumbes, Iquitos, and Huancayo) to enhance adaptability and efficacy. The final tool will be applied to older adults (60+) in the community by CHW. PHASE II: To assess the accuracy and acceptability, and characterization of older adults (60+) at the population level in Peru (n≈32,000): Using the mHealth system developed in Phase I, assessments including AD8, RUDAS-PE, and PFAQ, will be conducted. Accuracy for dementia diagnosis will be determined through gold-standard assessments involving interviews, neuropsychological testing, and the CDR in a subgroup of participants conducted by neurologists. The system will also collect data on socio-demographic information, carers, co-morbidities, quality of life, resource usage and costs. Phase III. To integrate the mHealth diagnostic system into Peru's primary healthcare (PHC) level: After validation, a 3-month quasi-experimental study in 2 centres per region will assess system performance, using waiting room recruitment and provider-conducted screenings for older adults. Indicators will evaluate integration success, sensitivity, and specificity of the tool, cost-effectiveness, and stakeholder perspectives through a process evaluation, guiding future scalability. RESULT: Early phases suggest that the IMPACT Dementia project will offer insights into dementia challenges in Peru. The co-design phase prioritises cultur

Journal article

Reed CN, Benito AL, Caspe F, Mcpherson APet al., 2024,

Shifting Ambiguity, Collapsing Indeterminacy: Designing with Data as Baradian Apparatus

, ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION, Vol: 31, ISSN: 1073-0516

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Citations: 6

Journal article

Chen L, Zuo H, Cai Z, Yin Y, Zhang Y, Sun L, Childs PRN, Wang Bet al., 2024,

Towards controllable generative design: a conceptual design generation approach leveraging the FBS ontology and Large Language Models

, Journal of Mechanical Design, Vol: 146, ISSN: 1050-0472

Recent research in the field of design engineering is primarily focusing on using AI technologies such as Large Language Models (LLMs) to assist early-stage design. The engineer or designer can use LLMs to explore, validate and compare thousands of generated conceptual stimuli and make final choices. This was seen as a significant stride in advancing the status of the generative approach in computer-aided design. However, it is often difficult to instruct LLMs to obtain novel conceptual solutions and requirement-compliant in real design tasks, due to the lack of transparency and insufficient controllability of LLMs. This study presents an approach to leverage LLMs to infer Function-Behavior-Structure (FBS) ontology for high-quality design concepts. Prompting design based on the FBS model decomposes the design task into three sub-tasks including functional, behavioral, and structural reasoning. In each sub-task, prompting templates and specification signifiers are specified to guide the LLMs to generate concepts. User can determine the selected concepts by judging and evaluating the generated function-structure pairs. A comparative experiment has been conducted to evaluate the concept generation approach. According to the concept evaluation results, our approach achieves the highest scores in concept evaluation, and the generated concepts are more novel, useful, functional, and low-cost compared to the baseline.

Journal article

Murphy R, Thillaithevan D, Hewson R, Santer Met al., 2024,

Multiscale structural optimization for prescribed deformations in the nonlinear elastic regime

, Structural and Multidisciplinary Optimization: computer-aided optimal design of stressed solids and multidisciplinary systems, Vol: 67, ISSN: 1615-147X

In this paper, a multiscale structural optimization framework capable of efficiently designing two-scale structures with prescribed displacements in the nonlinear elastic regime is presented. In contrast to previous multiscale structural optimization frameworks, which are founded upon the assumptions of linear elasticity, the present framework is capable of efficiently operating within the nonlinear elastic regime. At the core of the present framework is a parameterized microscale geometry, which through the straightforward manipulation of the microscale parameters provides direct access to both positive and negative Poisson’s ratios. The microscale model is concurrently coupled to the macroscale model such that only the microscale parameter space traversed by the optimizer is resolved during the optimization procedure, leading to a significant reduction in the computational expense of analysis. To demonstrate the capability of this framework, three prescribed deformation profiles are targeted by three distinct optimization procedures. In all instances, the deformation profile is successfully targeted. To verify the accuracy of the optimized structures, high-fidelity single-scale simulations are performed. In each case, excellent agreement is noted between the high-fidelity simulations and the corresponding optimized macroscale displacement fields, with errors of less than 10%.

Journal article

Baker CE, Martin P, Montemeglio A, Li R, Wilson M, Sharp DJ, Ghajari Met al., 2024,

Inherent uncertainty in pedestrian collision reconstruction: How evidence variability affects head kinematics and injury prediction

, ACCIDENT ANALYSIS AND PREVENTION, Vol: 208, ISSN: 0001-4575

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Journal article

Baker CE, Yu X, Lovell B, Tan R, Patel S, Ghajari Met al., 2024,

How well do popular bicycle helmets protect from different types of head injury?

, Annals of Biomedical Engineering, Vol: 52, Pages: 3326-3364, ISSN: 0090-6964

Bicycle helmets are designed to protect against skull fractures and associated focal brain injuries, driven by helmet standards. Another type of head injury seen in injured cyclists is diffuse brain injuries, but little is known about the protection provided by bicycle helmets against these injuries. Here, we examine the performance of modern bicycle helmets in preventing diffuse injuries and skull fractures under impact conditions that represent a range of real-world incidents. We also investigate the effects of helmet technology, price, and mass on protection against these pathologies. 30 most popular helmets among UK cyclists were purchased within 9.99-135.00 GBP price range. Helmets were tested under oblique impacts onto a 45° anvil at 6.5 m/s impact speed and four locations, front, rear, side, and front-side. A new headform, which better represents the average human head's mass, moments of inertia and coefficient of friction than any other available headforms, was used. We determined peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and BrIC. We also determined the risk of skull fractures based on PLA (linear risk), risk of diffuse brain injuries based on BrIC (rotational risk), and their mean (overall risk). Our results show large variation in head kinematics: PLA (80-213 g), PRV (8.5-29.9 rad/s), PRA (1.6-9.7 krad/s2), and BrIC (0.17-0.65). The overall risk varied considerably with a 2.25 ratio between the least and most protective helmet. This ratio was 1.76 for the linear and 4.21 for the rotational risk. Nine best performing helmets were equipped with the rotation management technology MIPS, but not all helmets equipped with MIPS were among the best performing helmets. Our comparison of three tested helmets which have MIPS and no-MIPS versions showed that MIPS reduced rotational kinematics, but not linear kinematics. We found no significant effect of helmet price on exposure-adjusted inju

Journal article

Weber ML, Jennings D, Šmíd B, Kindelmann M, Fearn S, Cavallaro A, Gutsche A, Heymann L, Yasin L, Cooper SJ, Skinner SJ, Dittmann R, Aguadero A, Fang X, Lenser C, Nemšák S, Gunkel Fet al., 2024,

Space Charge Effects on the Reaction Kinetics of Metal Exsolution and the Coalescence of Exsolved Nanoparticles

, ECS Meeting Abstracts, Vol: MA2024-02, Pages: 5113-5113

<jats:p> Metal exsolution reactions can be driven in fuel electrode materials under the reducing operation conditions of solid oxide cells. The process enables the synthesis of nanostructured catalysts based on the release of a fraction of reducible dopants from a perovskite host to its’ surface and the subsequent nucleation of finely dispersed oxide-supported metal nanoparticles. The performance of such catalysts strongly depends on the nanoparticle characteristics, such as the nanoparticle size and nanoparticle density.</jats:p> <jats:p>Consequently, dynamic structural and chemical changes of catalyst materials under operation conditions, oftentimes particularly affecting the catalyst surface <jats:italic>i.e.</jats:italic> the electrochemical interface, play a crucial role for the activity and stability of electrocatalysts. It is essential to understand the mechanistic processes that govern the material response to improve the lifetime of energy conversion devices such as water splitting catalysts or solid oxide cells.</jats:p> <jats:p>We employ epitaxial thin films with atomically defined surface morphologies to study the exsolution kinetics with respect to the mass transport of Ni dopants from the bulk to the perovskite surface. In addition, we investigate the subsequent growth and coalescence behavior of the exsolved nanoparticles during thermal reduction of the thin film samples. For this purpose, different approaches of defect-engineering are explored to investigate the role of donor-type and acceptor-type defect chemistry as well as the role of dislocations for exsolution reactions.</jats:p> <jats:p>We demonstrate that the electrostatic interactions of exsolution-active dopants with the surface potential that is correlated to the inherent surface space charge region of perovskite oxides determines the kinetics of metal exsolution in our material system. M

Journal article

Perera WHK, Webb T, Xu Y, Zhu J, Zhou Y, Trindade GF, Masteghin MG, Harvey SP, Jenatsch S, Dai L, Sathasivam S, Macdonald TJ, Hinder SJ, Zhao Y, Stranks SD, Zhao D, Zhang W, Jayawardena KDGI, Haque SA, Silva SRPet al., 2024,

23.2% efficient low band gap perovskite solar cells with cyanogen management

, ENERGY & ENVIRONMENTAL SCIENCE, ISSN: 1754-5692

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Conference paper

Yin Y, Wang B, Zuo H, Childs Pet al., 2024,

Effects of different human-in-the-loop approaches on human-ai co-design: a comparison between human-learning HITL approach and machine-learning HITL approach

, 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference-IDETC-CIE, Publisher: ASME

The speed at which the quantity of data is increasing stymies the deployment of some AI tools for design as the basis for training the tools is not stable. Also, selecting which data can be used as training data is a challenge. To address these issues, the concept of human-in-the-loop (HITL) approaches have been proposed. HITL includes human knowledge in the model-building processes to mitigate the high volume requirement of training data. Although how to apply AI in a design process and the effect of Generative AI tools (such as ChatGPT and Midjourney) in design processes has been explored, limited attention has been given to how different HITL approaches affect design performance. This study thus aimed to explore how different HITL approaches (Human-learning HITL approach and Machine-learning HITL approach) affect solutions of human-AI co-design. Fifteen participants were recruited to undertake two design tasks under the guidelines of Human-learning HITL and Machine-learning HITL approach respectively. The solutions from participants were assessed using four criteria (novelty, aesthetics, functionality, and feasibility). The results of the study indicated that the solution generated from Human-learning HITL approach is better compared with that of the Machine-learning HITL approach, especially in terms of aesthetics and functionality of the solution. The study supports the importance of expressing human insights through prompts on improving human-AI co-design solutions compared with providing more training data to AI.

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Journal article

Weber ML, Jennings D, Fearn S, Cavallaro A, Prochazka M, Gutsche A, Heymann L, Guo J, Yasin L, Cooper SJ, Mayer J, Rheinheimer W, Dittmann R, Waser R, Guillon O, Lenser C, Skinner SJ, Aguadero A, Nemšák S, Gunkel Fet al., 2024,

Thermal stability and coalescence dynamics of exsolved metal nanoparticles at charged perovskite surfaces

, Nature Communications, Vol: 15, ISSN: 2041-1723

Exsolution reactions enable the synthesis of oxide-supported metal nanoparticles, which are desirable as catalysts in green energy conversion technologies. It is crucial to precisely tailor the nanoparticle characteristics to optimize the catalysts’ functionality, and to maintain the catalytic performance under operation conditions. We use chemical (co)-doping to modify the defect chemistry of exsolution-active perovskite oxides and examine its influence on the mass transfer kinetics of Ni dopants towards the oxide surface and on the subsequent coalescence behavior of the exsolved nanoparticles during a continuous thermal reduction treatment. Nanoparticles that exsolve at the surface of the acceptor-type fast-oxygen-ion-conductor SrTi0.95Ni0.05O3−δ (STNi) show a high surface mobility leading to a very low thermal stability compared to nanoparticles that exsolve at the surface of donor-type SrTi0.9Nb0.05Ni0.05O3−δ (STNNi). Our analysis indicates that the low thermal stability of exsolved nanoparticles at the acceptor-doped perovskite surface is linked to a high oxygen vacancy concentration at the nanoparticle-oxide interface. For catalysts that require fast oxygen exchange kinetics, exsolution synthesis routes in dry hydrogen conditions may hence lead to accelerated degradation, while humid reaction conditions may mitigate this failure mechanism.

Journal article

Yin Y, Childs P, 2024,

A study of cognitive factor sequences and relations to creativity quality levels

, Humanities & Social Sciences Communications, Vol: 11, ISSN: 2662-9992

Cognitive factors such as association, memory, and combination have been verified to be related to the creative design process. However, limited research has considered the effects of cognitive factors and their interaction on creative processes in practical creative design processes. This study aimed to detect the interactive effects of cognitive factors on creative processes in a practical creative design process. In particular, how the sequence of cognitive factors affects creativity quality levels of the creative solutions was investigated. Seventy-one participants were recruited to undertake a design task using the think-aloud method. The results of this study are as follows. (i) The sequences of cognitive factors can contribute to different creativity quality levels of solutions. The sequence of semantic memory, common association, remote association, episodic memory, remote combination, idea expression, and idea evaluation is more likely to lead to a higher creativity quality level of solutions. (ii) The repetition of the same cognitive factor in a creative design process, especially semantic memory, does not necessarily contribute to a high-creativity-quality-level solution. (iii) Creativity quality levels of solutions are related to how many cognitive factors categories are involved in the creative design process. The more cognitive factors included, the higher the creativity quality of the solutions will be.

Journal article

Mulvey B, Nanayakkara T, 2024,

HAVEN: haptic and visual environment navigation by a shape-changing mobile robot with multimodal perception

, Scientific Reports, Vol: 14, ISSN: 2045-2322

Many animals exhibit agile mobility in obstructed environments due to their ability to tune their bodies to negotiate andmanipulate obstacles and apertures. Most mobile robots are rigid structures and avoid obstacles where possible. In this work,we introduce a new framework named Haptic And Visual Environment Navigation (HAVEN) Architecture to combine vision andproprioception for a deformable mobile robot to be more agile in obstructed environments. The algorithms enable the robot to beautonomously a) predictive by analysing visual feedback from the environment and preparing its body accordingly, b) reactiveby responding to proprioceptive feedback, and c) active by manipulating obstacles and gap sizes using its deformable body.The robot was tested approaching differently sized apertures in obstructed environments ranging from greater than its shapeto smaller than its narrowest possible size. The experiments involved multiple obstacles with different physical properties.The results show higher navigation success rates and an average 32% navigation time reduction when the robot activelymanipulates obstacles using its shape-changing body.

Journal article

Qiu D, Strbac G, Wang Y, Ye Y, Wang J, Pinson P, Silva V, Teng Fet al., 2024,

Artificial intelligence for microgrid resilience: a data-driven and model-free approach

, IEEE Power and Energy Magazine, Vol: 22, Pages: 18-27, ISSN: 1540-7977

Extreme weather events, which are characterized by high impact and low probability, can disrupt power system components and lead to severe power outages. The increasing adoption of renewable energy resources in the power sector, as part of decarbonization efforts, introduces further system operation challenges because of their fluctuating nature, potentially worsening the impact of these extreme weather events. To address the challenges from these high-impact and low-probability events, the concept of resilience has been introduced into the power industry. Considering the potential serious disruptions, the primary goal of resilient power system operation during extreme events is to ensure the continuous supply of critical loads, such as hospitals, police stations, data centers, traffic lights, etc., across various power sectors, which constitutes a system-wide load restoration problem.

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Journal article

Sadek M, Calvo R, Mougenot C, 2024,

Designing value-sensitive AI: a critical review and recommendations for socio-technical design processes

, AI and Ethics, Vol: 9, Pages: 949-967, ISSN: 2730-5961

This paper presents a critical review of how different socio-technical design processes for AI-based systems, from scholarly works and industry, support the creation of value-sensitive AI (VSAI). The review contributes to the emerging field of human-centred AI, and the even more embryonic space of VSAI in four ways: (i) it introduces three criteria for the review of VSAI based on their contribution to design processes’ overall value-sensitivity, and as a response to criticisms that current interventions are lacking in these aspects: comprehensiveness, level of guidance offered, and methodological value-sensitivity, (ii) it provides a novel review of socio-technical design processes for AI-based systems, (iii) it assesses each process based on the mentioned criteria and synthesises the results into broader trends, and (iv) it offers a resulting set of recommendations for the design of VSAI. The objective of the paper is to help creators and followers of design processes—whether scholarly or industry-based—to understand the level of value-sensitivity offered by different socio-technical design processes and act accordingly based on their needs: to adopt or adapt existing processes or to create new ones.

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Journal article

Cutting J, Deterding S, 2024,

The task-attention theory of game learning: a theory and research agenda

, Human-Computer Interaction, Vol: 39, Pages: 257-287, ISSN: 0737-0024

Why do learning games fail or succeed? Recent evidence suggests that attention forms an important moderator of learning from games. While existing media effects and learning theories acknowledge the role of attentional limits, they fail to account for the specific ways that games as interactive media steer attention. In response, we here develop the Task-Attention Theory of Game Learning. Drawing on current psychological and games research, task-attention theory argues that games as interactive media demand and structure the pursuit of tasks, which ties into distinct attentional mechanisms, namely learned attentional sets which focus attentional selection onto task-relevant features, as well as active sampling: users navigate and manipulate the game to elicit task-relevant information. This active sampling and selection precedes and moderates what information can be learned. We identify task-related game features (mechanics, goals, rewards and uncertainty) and demands (cognitive and perceptual load, pressure) that affect active sampling and attentional selection. We articulate implications and future work for game-based learning research and design, as well as wider media effects, learning, and HCI research.

Journal article

Almukhtar A, Batcup C, Bowman M, Winter Beatty J, Leff D, Demirel P, Judah G, Porat Tet al., 2024,

Interventions to achieve environmentally sustainable operating theatres: an umbrella systematic review using the behaviour change wheel

, International Journal of Surgery, Vol: 110, Pages: 7245-7267, ISSN: 1743-9159

Introduction: The healthcare sector is a major contributor to the climate crisis, and operating theatres (OTs) are one of the highest sources of emissions. To inform emissions reduction, this study aimed to (i) compare the outcomes of interventions targeting sustainable behaviours in OTs using the Triple Bottom Line framework, (ii) categorise the intervention strategies using the 5Rs (reduce, recycle, reuse, refuse, and renew) of circular economy, and (iii) examine Intervention Functions (IFs) using the Behaviour Change Wheel (BCW).Methods: Medline, Embase, PsychInfo, Scopus, and Web of Science databases were searched until June 2023 using the concepts: sustainability and surgery. The review was conducted in line with the Cochrane and Joanna Briggs Institution’s recommendations and was registered on PROSPERO. The results were reported in line with PRISMA, Supplemental Digital Content 1, https://links.lww.com/JS9/D210 (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines.Results: Sixteen reviews encompassing 43 life-cycle analyses, 30 interventions, 5 IFs, and 9 BCW policy categories were included. 28/30 (93%) interventions successfully led to sustainability improvements; however, the environmental outcomes were not suitable for meaningful comparisons due to their using different metrics and dependence on local factors. The ‘reduce’ strategy was the most prolific and commonly achieved through ‘education’ and/or ‘environmental restructuring’. However, single-session educational interventions were ineffective. Improving recycling relied on ‘environmental restructuring’. More intensive strategies such as ‘reuse’ require multiple intervention functions to achieve, either through a sustainability committee or through an intervention package.Conclusion: Policymakers must examine interventions within the local context. Comparing the outcomes of different interventions is difficult an

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Journal article

Chen L, Zhang Y, Han J, Sun L, Childs P, Wang Bet al., 2024,

A foundation model enhanced approach for generative design in combinational creativity

, Journal of Engineering Design, Vol: 35, Pages: 1394-1420, ISSN: 0954-4828

In creativity theory, combining two unrelated concepts into a novel idea is a common means of enhancing creativity. Designers can integrate the Additive concept into the Base concept to inspire and facilitate creative tasks. However, conceiving high-quality combinational ideas poses a challenge that combinational creativity itself demands the consideration of conceptual reasoning and synthesis. We propose an AI foundation model enhanced approach for supporting combinational creativity. This approach derives combinational embodiments, and assists humans in verbalising and externalising combinational ideas. Our experimental study demonstrates that the generated combinational ideas by the approach obtained highest scores compared to those ideas generated without an AI foundation model or combinational strategy. We built a combinational creativity tool called CombinatorX based on this approach to generate ideas. In a study with the comparison of an existing combinational creativity tool and Internet search, we validated that our approach improves the effectiveness of combinational idea generation, enables a reduction in labour force, and facilitates the refinement of combinational ideation.

Journal article

Ge Y, Zong R, Chen X, Nanayakkara Tet al., 2024,

An origami-inspired endoscopic capsule with tactile perception for early tissue anomaly detection

, IEEE Robotics and Automation Letters, Vol: 9, Pages: 10018-10025, ISSN: 2377-3766

Video Capsule Endoscopy (VCE) is currently one of the most effective methods for detecting intestinal diseases. However, it is challenging to detect early-stage small nodules with this method because they lack obvious color or shape features. In this letter, we present a new origami capsule endoscope to detect early small intestinal nodules using tactile sensing. Four soft tactile sensors made out of piezoresistive material feed four channels of phase-shifted data that are processed using a particle filter. The particle filter uses an importance assignment template designed using experimental data from six known sizes of nodules. Moreover, the proposed capsule can use shape changes to move forward or backward under peristalsis passively. In the experiment, it was able to return to a specific area for repeated detection in a straight, two-dimensional intestinal model. Experimental results show that the proposed capsule can detect nodules of more than 3 mm diameter with 100% accuracy.

Challenges in Value-Sensitive AI Design: Insights from AI Practitioner Interviews

Data-driven robust optimisation of hydrogen infrastructure planning under demand uncertainty using a hybrid decomposition method

A Fast Forward Prediction Framework for Energy Materials Design Based on Machine Learning Methods

Codesigning AI with End-Users: An AI Literacy Toolkit for Nontechnical Audiences (Jul, 10.1093/iwc/iwae029, 2024)

Li-ion battery design through microstructural optimization using generative AI

Microstructure Characterization of Battery Materials Based on Voxelated Image Data: Computation of Active Surface Area and Tortuosity

Preface II

Preface I

Handbook on soft robotics

Introduction

Soft robots as a platform to understand embodied intelligence

Confutation of the “Counterexample to passivity preservation for variable impedance control of compliant robots”

Public Health.

Shifting Ambiguity, Collapsing Indeterminacy: Designing with Data as Baradian Apparatus

Towards controllable generative design: a conceptual design generation approach leveraging the FBS ontology and Large Language Models

Multiscale structural optimization for prescribed deformations in the nonlinear elastic regime

Inherent uncertainty in pedestrian collision reconstruction: How evidence variability affects head kinematics and injury prediction

How well do popular bicycle helmets protect from different types of head injury?

Space Charge Effects on the Reaction Kinetics of Metal Exsolution and the Coalescence of Exsolved Nanoparticles

23.2% efficient low band gap perovskite solar cells with cyanogen management

Effects of different human-in-the-loop approaches on human-ai co-design: a comparison between human-learning HITL approach and machine-learning HITL approach

Thermal stability and coalescence dynamics of exsolved metal nanoparticles at charged perovskite surfaces

A study of cognitive factor sequences and relations to creativity quality levels

HAVEN: haptic and visual environment navigation by a shape-changing mobile robot with multimodal perception

Artificial intelligence for microgrid resilience: a data-driven and model-free approach

Designing value-sensitive AI: a critical review and recommendations for socio-technical design processes

The task-attention theory of game learning: a theory and research agenda

Interventions to achieve environmentally sustainable operating theatres: an umbrella systematic review using the behaviour change wheel

A foundation model enhanced approach for generative design in combinational creativity

An origami-inspired endoscopic capsule with tactile perception for early tissue anomaly detection

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