A new approach for climbing hard vertical surfaces has been developed that allows a robot to scale concrete, stucco, brick and masonry walls without using suction or adhesives. The approach is inspired by the mechanisms observed in some climbing insects and spiders and involves arrays of microspines that catch on surface asperities. The arrays are located on the toes of the robot and consist of a tuned, multi-link compliant suspension. The fundamental issues of spine allometric scaling versus surface roughness are discussed and the interaction between spines and surfaces is modeled. The toe suspension properties needed to maximize the probability that each spine will find a useable surface irregularity and to distribute climbing loads among many spines are detailed. The principles are demonstrated with a new climbing robot, SpinybotII, that can scale a wide range of flat exterior walls, carry a payload equal to its own weight, and cling without consuming power. The paper also reports how toe parameters scale with robot mass and how spines have also been used successfully on the larger RiSE robot

Abstract-A new approach for climbing hard vertical surfaces has been developed that allows a robot to scale concrete, stucco, brick and masonry walls without using suction or adhesives. The approach is inspired by the mechanisms observed in some climbing insects and spiders and involves arrays of microspines that catch on surface asperities. The arrays are located on the toes of the robot and consist of a tuned, multi-link compliant suspension. In this paper we discuss the fundamental issues of spine allometric scaling versus surface roughness and the suspension needed to maximize the probability that each spine will find a useable surface irregularity and to distribute climbing tensile and shear loads among many spines. The principles are demonstrated with a new climbing robot that can scale a wide range of exterior walls.

The diffusion of innovative working process, including rapid prototyping techniques, is needed to achieve sustainable production technology. Selective Laser Sintering (SLS) has a potential as an environmental benign alternative to traditional processes but only few authors deal with the process optimisation including energy aspects. In the present paper an analysis of the energetic aspect of SLS is proposed. In addition, with respect to the classical technological parameters (resolution, productivity) attention is paid to energetic elements (energetic productivity, laser parameters) showing how the perspective of a sensible development of such a kind of technology could be beneficial not only from a technological point of view, but also for energy saving in a lot of manufacturing fields. A polyamide powder is the material tested to acquire some characteristics data of the process. It is shown that the energy intensity of the process in optimal condition could be of the order of 0.2 J for each mm 3 of material agglomerated.

The emerging of the fourth industrial revolution, also known as Industry 4.0 (I4.0), from the advancement in several technologies is viewed not only to promote economic growth, but also to enable a greener future. The 2030 Agenda of the United Nations for sustainable development sets out clear goals for the industry to foster the economy, while preserving social well-being and ecological validity. However, the influence of I4.0 technologies on the achievement of the Sustainable Development Goals (SDG) has not been conclusively or systematically investigated. By understanding the link between the I4.0 technologies and the SDGs, researchers can better support policymakers to consider the technological advancement in updating and harmonizing policies and strategies in different sectors (i.e., education, industry, and governmental) with the SDGs. To address this gap, academic experts in this paper have investigated the influence of I4.0 technologies on the sustainability targets identified by the UN. Key I4.0 element technologies have been classified to enable a quantitative mapping with the 17 SDGs. The results indicate that the majority of the I4.0 technologies can contribute positively to achieving the UN agenda. It was also found that the effects of the technologies on individual goals varies between direct and strong, and indirect and weak influences. The main insights and lessons learned from the mapping are provided to support future policy.

The main goal of the minimum zone tolerance (MZT) method is to achieve the best estimation of the roundness error, but it is computationally intensive. This paper describes the application of a genetic algorithm (GA) to minimize the computation time in the evaluation of CMM roundness errors of a large cloud of sampled datapoints (0.2° equally spaced datapoints). Computational experiments have shown that by selecting the optimal GA parameters, namely a combination of the four genetic parameters related to population size, crossover, mutation, and stop conditions, the computation time can be reduced by up to one order of magnitude, allowing realtime operation. Optimization has been tested using seven CMM datasets, obtained from different machining features, and compared with the LSQ method. The performance of the optimized algorithm has been validated with GA from the literature using four benchmark datasets.