BioForms integrates sacrificial formworks, agent-based computational algorithms and biological growth in the generation of biodegradable internal wall panel systems. These wall panel systems are intended to minimize material waste, utilize local botany and generate a symbiosis between the artificially made and the naturally grown. This is achieved by utilizing local waste as a structural compressive core, mycelium as the binder, and recycled pellets as the architectural skin. Leveraging mycelium’s structural, acoustic and thermal properties, this exploration delves into unique methods of incorporating fungi and waste into architectural construction. The motivations for this research stem from the need to address the building industry’s contribution to climate change, by considering the lifecycle of our materials. BioForms aims to retrofit existing buildings by replacing foam insulation and MDF (medium-density fiberboard) wall panels with biodegradable and recyclable 3D-printed skins embedded with a mycelium core. Analysing mycelium’s reaction to BioForms I, the second iteration, BioForms II, evolves in design complexity and materiality. BioForms II explored robotically fabricated wood-based polylactic acid plastic (PLA) composite materials. Within the second iteration of this research stream, mycelia was both embedded within the compressed fabricated skins and on the external surface. Whilst BioForms explored the generation of biodegradable wall panel systems, the broader aims of this research is aimed at infiltrating biological matter into human-occupied spaces, completely omitting the use of synthetic building materials within the construction industry and advancing the architects relationship to nature in the generation of form.

This paper provides the methodology used to simulate and control an icosahedral tensegrity structure augmented with movable masses attached to each bar to provide a means of locomotion. The center of mass of the system can be changed by moving the masses along the length of each of the bars that compose the structure. Moving the masses changes the moments created by gravitational force, allowing for the structure to roll. With this methodology in mind, a controller was created to move the masses to the desired locations to cause such a roll. As shown later in this paper, such a methodology, assuming the movable masses have the required mass, allows for full control of the system using a quasi-static controller created specifically for this system. This system has advantages over traditional tensegrity controllers because it retains its shape and is designed for high-shock scenarios.

Sustainability is becoming a major strategic driver within the aviation industry, which has moved from providing primarily economic benefits to delivering the ‘triple bottom line’, including social and environmental impact as well as financial performance. Sustainable aviation is also being tracked by the International Civil Aviation Organisation (ICAO) Global Collation for Sustainable Aviation. Operations and Infrastructure is an important near-term opportunity to deliver sustainability benefits. Digital Technologies, Integrated Vehicle Health Management (IVHM) and Maintenance Repair and Overhaul (MRO) play a prominent role in implementing these benefits, with a particular focus on operational efficiencies. As part of this, the sustainable smart hangar of the future is a concept that is becoming more and more important in forming the future of the aviation industry. The Hangar of the Future is an excellent opportunity for innovation, combining the progress in manufacturing, materials, robotics and artificial intelligence technologies. Succeeding in developing a hangar with these characteristics will provide us with potential benefits ranging from reduced downtime and costs to improved safety and environmental impact. This work explores some of the key features related to the sustainable smart hangar of the future by discussing research that takes place in DARTeC’s (Digital Aviation Research and Technology Centre) hangar led by the IVHM Centre in Cranfield. Additionally, the paper touches on some longer-term aspirations.

We study whether the increased adoption of available automation technologies allows economies to avoid the negative effect of aging on per capita output. We develop a quantitative theory in which firms choose to which extent they automate in response to a declining workforce and rising old-age dependency. An important element in our model is the integration of two capital types: automation capital that acts as a substitute to human labor, and traditional capital that is a complement to labor. Empirically, our model's predictions largely match data regarding automation (robotization) density across OECD countries. Simulating the model, we find that aging-induced automation only partially compensates the negative growth effect of aging in the absence of technical progress in automation technology. One reason is that automated tasks are no perfect substitutes for non-automated tasks. A second reason is that automation raises the interest rate and thus inhibits positive behavioral reactions to aging (later retirement and investment in human capital). Moreover, increased automation generates a falling net labor share of income and rising welfare inequality. We evaluate alternative policy responses to cope with this inequality.

This systematic literature review paper, written by Channarong Intahchomphoo, Jason Millar, Odd Erik Gundersen, Christian Tschirhart, Kris Meawasige and Hojjat Salemi, examines academic research publications to learn about the effects of artificial intelligence (AI) and robotics on human labour. Papers were collected from three academic databases: Scopus, Web of Science and ABI/INFORM Collection. From 710 papers, 159 papers were included. The article finds that the effects of AI and robotics on human labour can be categorised as: (i) positive effects, (ii) negative effects, and (iii) neutral or unsure effects. The positive effects have five reasons regarding AI and robotics’ potential to: do dangerous work, do tedious work with high efficiency and accuracy, do some aspects of computing work, do work that human labour does not want to do and be used to deal with the labour shortage, and help to reduce business production and maintenance costs. The negative effects are based on two reasons, that AI and robotics will take over human labour in part or entirely, thereby creating unemployment crises, and will not only replace manually repetitive jobs from human labour but also cognitive jobs, causing human labour to fear that their jobs will be replaced by AI and robotics. The neutral and unsure effects are based on various unique arguments. The findings of this review are used to suggest future research for academic communities and practical recommendations to legal professionals and policy makers.

Handling and manipulating flexible porous objects is one of the main challenges in robotics for household and industrial tasks. Improving the design of grippers for flexible objects of manipulation is an important stage in the development of this topic. This article proposes a method of modeling a gripper for porous objects using the finite element method. It identifies the main parameters of the model that will affect the grasping force and the permeability of porous objects. The power characteristics of the obtained gripper model for different supply pressures, with varying porosity of the manipulated objects, are determined. The obtained characteristics are then used to find the correspondence of channel length for three textile materials with different permeable properties. An experimental study of the lifting force is conducted, and a comparison is made with the obtained modeling data for the presented samples. Additionally, using the obtained simulation data, an analysis of the pressure distribution on the surface of the porous object of manipulation is performed. As a result, it is found that the gripping device must use a design with elements to stabilize the distribution of pressure in its chamber, which will increase the stability of the gripping process.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

Current national and international guidelines for the ethical design and development of artificial intelligence (AI) and robotics emphasize ethical theory. Various governing and advisory bodies have generated sets of broad ethical principles, which institutional decisionmakers are encouraged to apply to particular practical decisions. Although much of this literature examines the ethics of designing and developing AI and robotics, medical institutions typically must make purchase and deployment decisions about technologies that have already been designed and developed. The primary problem facing medical institutions is not one of ethical design but of ethical deployment. The purpose of this paper is to develop a practical model by which medical institutions may make ethical deployment decisions about ready-made advanced technologies. Our slogan is “more process, less principles.” Ethically sound decisionmaking requires that the process by which medical institutions make such decisions include participatory, deliberative, and conservative elements. We argue that our model preserves the strengths of existing frameworks, avoids their shortcomings, and delivers its own moral, practical, and epistemic advantages.

To support and facilitate the rehabilitation of patients with physical limitations and aid the therapist, several robotic structures are being studied. Among the structures, the cable-driven robots stand out. The cable-driven robots are structures actuated by cables and have the advantages of being flexible and reconfigurable for each patient. The objective of this paper is to develop a theoretical model for knee flexion/extension force and moment using a cable-driven robot. The proposed model is necessary for elaborating a referential to which diagnosis can be made and the improvement of the patient evaluated. The presented theoretical model was validated through experiments with twelve sedentary and healthy volunteers. The first procedure tested ten subjects in three thigh angles for knee flexion motion; the second procedure tested two subjects in flexion and extension for the same thigh angle. The results show the validity of the model for 88.58% of the tests in an ANOVA analysis with a 99% confidence interval. The similarity of data for different gender, ages, and intrinsic factors was noted, implying that the model is representative and independent of the subject’s individuality. Differences between flexion and extension values were observed, which need to be studied in the future.