Recent textile innovations have significantly transformed both the material structures of fibers and fabrics as well as their sphere of use and applications.At the same time, new recycling concepts and methods to re--use textile waste are rapidly being developed and many new ways to make use of recycled and reclaimed fibers have already been found. In this paper, we describe how the development of a new textile, making use of recycled fibers, sparked the development of Textile Reflexes, a robotic textile that can change shape. This paper elaborates on the development of the new textile material, the multidisciplinary approach we take to advance it towards a robotic textile and our first endeavours to implement it in a health & wellbeing context. Textile Reflexes was applied in a vest that supports posture correction and training that was evaluated in a user study. In this way, the paper demonstrates a material and product design study that bridges disciplines and that links to both environmental and social change.doi: 10.21606/dma.2017.610This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License. https://creativecommons.org/licenses/by-nc-sa/4.0/
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The estimation of the pose of a differential drive mobile robot from noisy odometer, compass and beacon distance measurements is studied. The estimation problem, which is a state estimation problem with unknown input, is reformulated into a state estimation problem with known input and a process noise term. A heuristic sensor fusion algorithm solving this state-estimation problem is proposed and compared with the extended Kalman filter solution and the Particle Filter solution in a simulation experiment. https://doi.org/10.4018/IJAIML.2020010101 https://www.linkedin.com/in/john-bolte-0856134/
Abstract Long-haul travel does not constitute an obstacle for tourists to travel and is fast gaining the attention of tourists in new and unique experiences. This study was conducted to identify the long-haul travel motivation by international tourists to Penang. A total of 400 respondents participated in this survey, conducted around the tourist attractions in Penang, using cluster random sampling. However, only 370 questionnaires were only used for this research. Data were analysed using SPSS software 22 version. The findings, ‘knowledge and novelty seeking’ were the main push factors that drove long-haul travel by international tourists to Penang. Meanwhile, the main pull factor that attracts long- haul travel by international tourists to Penang was its ‘culture and history’. Additionally, there were partly direct and significant relationships between socio-demographic, trip characteristics and travel motivation (push factors and pull factors). Overall, this study identified the long-haul travel motivations by international tourists to Penang based on socio-demographic, trip characteristics and travel motivation and has indirectly helped in understanding the long-haul travel market particularly for Penang and Southeast Asia. This research also suggested for an effective marketing and promotion strategy in pro- viding useful information that is the key to attract international tourists to travel long distances. Keywords:
Even though considerable amounts of valuable wood are collected at waste collection sites, most of it remains unused and is burned: it is too labor-intensive to sort, process and upcycle useable parts. Valuable wood thus becomes worthless waste, against circular economy principles. In MoBot-Wood, waste collection organizations HVC and the municipality of Amsterdam, together with Rolan Robotics, Metabolic and AUAS investigate how waste wood can be sorted and processed at waste collection sites, using an easy-to-deploy robotic solution. In various preceding and on-going projects, AUAS and partners are exploring circular wood intake, sorting and processing using industrial robots, including processes like machine vision, 3D scanning, sawing, and milling. These projects show that harvesting waste wood is a challenging matter. Generally, the wood is only partially useable due to the presence of metal, excessive paint, deterioration by fungi and water, or other contamination and damages. To harvest useable wood thus requires intensive sorting and processing. The solution of transporting all the waste wood from collection sites to a central processing station might be too expensive and have a negative environmental impact. Considering that much of collected wood will need to be discarded, often no wood is harvested at all, due to the costs for collection and shipping. Speaking with several partners in related projects, the idea emerged to develop a mobile robotic station, which can be (temporarily) deployed at waste collection sites, to intake, sort and process wood for upcycling. In MoBot-Wood, research entails the design of such station, its deployment conditions, and a general assessment of its potential impact. The project investigates robotic sorting and processing on location as a new approach to increase the amount of valuable, useable wood harvested at waste collection sites, by avoiding material transport and reducing the volume of remaining waste.
