Smart knife: technological advances towards smart cutting tools in meat industry automation

Purpose Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined. Design/methodology/approach This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife. Findings Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability. Originality/value This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.Smart knife: technological advances towards smart cutting tools in meat industry automationpublishedVersio

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Proceedings of the 2012 Workshop on Ambient Intelligence Infrastructures (WAmIi)

This is a technical report including the papers presented at the Workshop on Ambient Intelligence Infrastructures (WAmIi) that took place in conjunction with the International Joint Conference on Ambient Intelligence (AmI) in Pisa, Italy on November 13, 2012. The motivation for organizing the workshop was the wish to learn from past experience on Ambient Intelligence systems, and in particular, on the lessons learned on the system architecture of such systems. A significant number of European projects and other research have been performed, often with the goal of developing AmI technology to showcase AmI scenarios. We believe that for AmI to become further successfully accepted the system architecture is essential

Ultra high frequency (UHF) radio-frequency identification (RFID) for robot perception and mobile manipulation

Personal robots with autonomy, mobility, and manipulation capabilities have the potential to dramatically improve quality of life for various user populations, such as older adults and individuals with motor impairments. Unfortunately, unstructured environments present many challenges that hinder robot deployment in ordinary homes. This thesis seeks to address some of these challenges through a new robotic sensing modality that leverages a small amount of environmental augmentation in the form of Ultra High Frequency (UHF) Radio-Frequency Identification (RFID) tags. Previous research has demonstrated the utility of infrastructure tags (affixed to walls) for robot localization; in this thesis, we specifically focus on tagging objects. Owing to their low-cost and passive (battery-free) operation, users can apply UHF RFID tags to hundreds of objects throughout their homes. The tags provide two valuable properties for robots: a unique identifier and receive signal strength indicator (RSSI, the strength of a tag's response). This thesis explores robot behaviors and radio frequency perception techniques using robot-mounted UHF RFID readers that enable a robot to efficiently discover, locate, and interact with UHF RFID tags applied to objects and people of interest. The behaviors and algorithms explicitly rely on the robot's mobility and manipulation capabilities to provide multiple opportunistic views of the complex electromagnetic landscape inside a home environment. The electromagnetic properties of RFID tags change when applied to common household objects. Objects can have varied material properties, can be placed in diverse orientations, and be relocated to completely new environments. We present a new class of optimization-based techniques for RFID sensing that are robust to the variation in tag performance caused by these complexities. We discuss a hybrid global-local search algorithm where a robot employing long-range directional antennas searches for tagged objects by maximizing expected RSSI measurements; that is, the robot attempts to position itself (1) near a desired tagged object and (2) oriented towards it. The robot first performs a sparse, global RFID search to locate a pose in the neighborhood of the tagged object, followed by a series of local search behaviors (bearing estimation and RFID servoing) to refine the robot's state within the local basin of attraction. We report on RFID search experiments performed in Georgia Tech's Aware Home (a real home). Our optimization-based approach yields superior performance compared to state of the art tag localization algorithms, does not require RF sensor models, is easy to implement, and generalizes to other short-range RFID sensor systems embedded in a robot's end effector. We demonstrate proof of concept applications, such as medication delivery and multi-sensor fusion, using these techniques. Through our experimental results, we show that UHF RFID is a complementary sensing modality that can assist robots in unstructured human environments.PhDCommittee Chair: Kemp, Charles C.; Committee Member: Abowd, Gregory; Committee Member: Howard, Ayanna; Committee Member: Ingram, Mary Ann; Committee Member: Reynolds, Matt; Committee Member: Tentzeris, Emmanoui

Analyse, modélisation et implémentation de stratégies d’assistance : déploiement d’orthèses cognitives pour les activités instrumentales de la vie quotidienne des traumatisés crâniens

De nos jours, les traumatismes cranio-cérébraux (TCC) sévères sont considérés comme un problème de santé publique au plan mondial. En effet, un TCC sévère engendre des répercussions importantes dans la vie des personnes l’ayant subi. Ces répercussions sont liées aux dysfonctionnements cognitifs, émotionnels et comportementaux. Ces troubles occasionnent une baisse, souvent très importante, de leur indépendance dans la réalisation des Activités Instrumentales de la Vie Quotidienne (AIVQ), telles que préparer un repas, gérer ses finances, utiliser son téléphone, conduire une automobile, faire des achats, etc. Très souvent, les personnes ayant subi un TCC sévère doivent retourner vivre au sein de leur domicile malgré les grandes difficultés liées à leur état. Les TCC sévères ressentiront très souvent le besoin d’assistance pour la réalisation des AIVQ. Cette thèse s’inscrit dans le cadre d’un grand projet de recherche financé par les Instituts de recherche en santé du Canada et le Conseil de Recherches en Sciences Naturelles et en Génie du Canada (CRSNG). En particulier, le Projet de Recherche Concertée sur la Santé (PRCS). L’objectif de cette thèse, au sein de ce projet, consiste à concevoir, représenter, formaliser et implémenter une structure d’assistance cognitive contextuelle et adaptative selon le profil des personnes atteintes de TCC sévère pour la réalisation des AIVQ. Cette assistance favorisera leur indépendance dans la réalisation des AIVQ au sein de leur domicile. La conception de cette assistance cognitive numérique implique un travail interdisciplinaire entre l’ergothérapie et l’informatique, afin de passer de la pratique d’assistance fournie par des cliniciens à la formulation formelle et à l’implémentation. Cette conception s’appuie sur une démarche de conception participative qui sollicite principalement les résidents d’un milieu d’hébergement alternatif domotisé.Abstract: Severe Traumatic Brain Injury (TBI) is considered a public health problem. Indeed, severe TBI causes significant cognitive, emotional and behavioral repercussions that impact the lives of these individuals, particularly their ndependence in Instrumental Activities of Daily Living (IADLs). Individuals who have experienced severe TBI frequently return to live in their homes despite the severe difficulties associated with their condition, though the need for assistance to perform IADLs frequently persists. The objective of this thesis is to design, represent, formalize and implement a context-aware and adaptive structure of cognitive assistance. This assistance is created according to the general needs of individuals with severe TBI for IADL performance. The proposed assistance will promote their independence to perform IADL in a home environment. The design of this cognitive assistance technology involves an interdisciplinary collaboration between occupational therapy and computer science, to evolve from the assistance provided by the clinicians to a formal computer science formulation and implementation. This design is based on a participative design approach that mainly involves TBI residents of a smart alternative housing unit. A prototype of a cognitive orthotic for meal preparation (COOK) was created and deployed within an alternative housing unit. Implementation of this cognitive orthotic lifted the prohibition on use of a stove for meal preparation that had previously been placed on their residents. By allowing these residents to cook independently, COOK has contributed to helping them become more independent in cooking and more confident in their ability to do so