Intuitive Instruction of Industrial Robots : A Knowledge-Based Approach

With more advanced manufacturing technologies, small and medium sized enterprises can compete with low-wage labor by providing customized and high quality products. For small production series, robotic systems can provide a cost-effective solution. However, for robots to be able to perform on par with human workers in manufacturing industries, they must become flexible and autonomous in their task execution and swift and easy to instruct. This will enable small businesses with short production series or highly customized products to use robot coworkers without consulting expert robot programmers. The objective of this thesis is to explore programming solutions that can reduce the programming effort of sensor-controlled robot tasks. The robot motions are expressed using constraints, and multiple of simple constrained motions can be combined into a robot skill. The skill can be stored in a knowledge base together with a semantic description, which enables reuse and reasoning. The main contributions of the thesis are 1) development of ontologies for knowledge about robot devices and skills, 2) a user interface that provides simple programming of dual-arm skills for non-experts and experts, 3) a programming interface for task descriptions in unstructured natural language in a user-specified vocabulary and 4) an implementation where low-level code is generated from the high-level descriptions. The resulting system greatly reduces the number of parameters exposed to the user, is simple to use for non-experts and reduces the programming time for experts by 80%. The representation is described on a semantic level, which means that the same skill can be used on different robot platforms. The research is presented in seven papers, the first describing the knowledge representation and the second the knowledge-based architecture that enables skill sharing between robots. The third paper presents the translation from high-level instructions to low-level code for force-controlled motions. The two following papers evaluate the simplified programming prototype for non-expert and expert users. The last two present how program statements are extracted from unstructured natural language descriptions

Assembly planning in cluttered environments through heterogeneous reasoning

Assembly recipes can elegantly be represented in description logic theories. With such a recipe, the robot can figure out the next assembly step through logical inference. However, before performing an action, the robot needs to ensure various spatial constraints are met, such as that the parts to be put together are reachable, non occluded, etc. Such inferences are very complicated to support in logic theories, but specialized algorithms exist that efficiently compute qualitative spatial relations such as whether an object is reachable. In this work, we combine a logic-based planner for assembly tasks with geometric reasoning capabilities to enable robots to perform their tasks under spatial constraints. The geometric reasoner is integrated into the logic-based reasoning through decision procedures attached to symbols in the ontology.Peer ReviewedPostprint (author's final draft

Robotic Automation of Turning Machines in Fenceless Production: A Planning Toolset for Economic-based Selection Optimization between Collaborative and Classical Industrial Robots

Ursprünglich wurden Industrieroboter hauptsächlich hinter Schutzzäunen betrieben, um den Sicherheitsanforderungen gerecht zu werden. Mit der Flexibilisierung der Produktion wurden diese scharfen Trennbereiche zunehmend aufgeweicht und externe Sicherheitstechnik, wie Abstandssensoren, genutzt, um Industrieroboter schutzzaunlos zu betreiben. Ausgehend vom Gedanken dieser Koexistenz bzw. Kooperation wurde die Sicherheitssensorik in den Roboter integriert, um eine wirkliche Kollaboration zu ermöglichen. Diese sogenannten kollaborierenden Roboter, oder Cobots, eröffnen neue Applikationsfelder und füllen somit die bestehenden Automatisierungslücken. Doch welche Automatisierungsvariante ist aus wirtschaftlichen Gesichtspunkten die geeignetste? Bisherige Forschung untersucht zum Großteil isoliert eine der beiden Technologien, ohne dabei einen Systemvergleich hinsichtlich technologischer Spezifika und Wirtschaftlichkeit anzustellen. Daher widmet sich diese Dissertation einer Methodik zum wirtschaftlichen Vergleich von kollaborierenden Robotern und Industrierobotern in schutzzaunlosen Maschinenbeladungssystemen. Besonderer Fokus liegt dabei auf dem Herausarbeiten der technischen Faktoren, die die Wirtschaftlichkeit maßgeblich beeinflussen, um ein Systemverständnis der wirtschaftlichen Struktur beider Robotertechnologievarianten zu erhalten. Zur Untersuchung werden die Inhalte eines solchen Planungsvorhabens beschrieben, kategorisiert, systematisiert und modularisiert. Auf wirtschaftlicher Seite wird ein geeignetes Optimierungsmodell vorgestellt, während auf technischer Seite vor allem die Machbarkeit hinsichtlich Greifbarkeit, Layoutplanung, Robotergeschwindigkeiten und Zykluszeitbestimmung untersucht wird. Mit deduktiven, simulativen, empirischen und statistischen Methoden wird das Systemverhalten für die einzelnen Planungsinhalte analysiert, um die Gesamtwirtschaftlichkeit mit einem Minimum an Investment,- Produktions,- und Zykluszeitinformationen a priori vorhersagen zu können. Es wird gezeigt, dass durch einen Reverse Engineering Ansatz die notwendigen Planungsdaten, im Sinne von Layoutkomposition, Robotergeschwindigkeiten und Taktzeiten, mithilfe von Frontloading zu Planungsbeginn zur Verfügung gestellt werden können. Dabei dient der Kapitalwert als wirtschaftliche Bewertungsgrundlage, dessen Abhängigkeit vom Mensch-Roboter-Interaktionsgrad in einem Vorteilhaftigkeitsdiagramm für die einzelnen Technologiealternativen dargestellt werden kann. Wirtschaftlich fundierte Entscheidungen können somit auf quantitiativer Basis getroffen werden.:1. Introduction 25 1.1 Research Domain 25 1.2 Research Niche 26 1.3 Research Structure 28 2. State of the Art and Research 31 2.1 Turning Machines and Machine Tending 31 2.1.1 Tooling Machine Market Trends and Machine Tending Systems 31 2.1.2 Workpiece System 34 2.1.3 Machine System 36 2.1.4 Logistics System 39 2.1.5 Handling System 41 2.2 Robotics 43 2.2.1 Robot Installation Development and Application Fields 43 2.2.2 Fenceless Industrial and Collaborative Robots 48 2.2.3 Robot Grippers 55 2.3 Planning and Evaluation Methods 56 2.3.1 Planning of General and Manual Workstations 56 2.3.2 Cell Planning for Fully Automated and Hybrid Robot Systems 59 2.3.3 Robot Safety Planning 61 2.3.4 Economic Evaluation Methods 70 2.4 Synthesis - State of the Art and Research 71 3. Solution Approach 77 3.1 Need for Research and General Solution Approach 77 3.2 Use Case Delineation and Planning Focus 80 3.3 Economic Module – Solution Approach 86 3.4 Gripper Feasibility Module – Solution Approach 89 3.5 Rough Layout Discretization Model – Solution Approach 94 3.6 Cycle Time Estimation Module – Solution Approach 97 3.7 Collaborative Speed Estimation Module – Solution Approach 103 3.7.1 General Approach 103 3.7.2 Case 1: Quasi-static Contact with Hand 107 3.7.3 Case 2: Transient Contact with Hand 109 3.7.4 Case 3: Transient Contact with Shoulder 111 3.8 Synthesis – Solution Approach 114 4. Module Development 117 4.1 Economic Module – Module Development 117 4.1.1 General Approach 117 4.1.2 Calculation Scheme for Manual Operation 117 4.1.3 Calculation Scheme for Collaborative Robots 118 4.1.4 Calculation Scheme for Industrial Robots 120 4.2 Gripper Feasibility Module – Module Development 121 4.3 Rough Layout Discretization Module – Module Development 122 4.3.1 General Approach 122 4.3.2 Two-Dimensional Layout Pattern 123 4.3.3 Three-Dimensional Layout Pattern 125 4.4 Cycle Time Estimation Module – Module Development 126 4.4.1 General Approach 126 4.4.2 Reachability Study 127 4.4.3 Simulation Results 128 4.5 Collaborative Speed Estimation Module – Module Development 135 4.5.1 General Approach 135 4.5.2 Case 1: Quasi-static Contact with Hand 135 4.5.3 Case 2: Transient Contact with Hand 143 4.5.4 Case 3: Transient Contact with Shoulder 145 4.6 Synthesis – Module Development 149 5. Practical Verification 155 5.1 Use Case Overview 155 5.2 Gripper Feasibility 155 5.3 Layout Discretization 156 5.4 Collaborative Speed Estimation 157 5.5 Cycle Time Estimation 158 5.6 Economic Evaluation 160 5.7 Synthesis – Practical Verification 161 6. Results and Conclusions 165 6.1 Scientific Findings and Results 165 6.2 Critical Appraisal and Outlook 173Initially, industrial robots were mainly operated behind safety fences to account for the safety requirements. With production flexibilization, these sharp separation areas have been increasingly softened by utilizing external safety devices, such as distance sensors, to operate industrial robots fenceless. Based on this idea of coexistence or cooperation, safety technology has been integrated into the robot to enable true collaboration. These collaborative robots, or cobots, open up new application fields and fill the existing automation gap. But which automation variant is most suitable from an economic perspective? Present research dealt primarily isolated with one technology without comparing these systems regarding technological and economic specifics. Therefore, this doctoral thesis pursues a methodology to economically compare collaborative and industrial robots in fenceless machine tending systems. A particular focus lies on distilling the technical factors that mainly influence the profitability to receive a system understanding of the economic structure of both robot technology variants. For examination, the contents of such a planning scheme are described, categorized, systematized, and modularized. A suitable optimization model is presented on the economic side, while the feasibility regarding gripping, layout planning, robot velocities, and cycle time determination is assessed on the technical side. With deductive, simulative, empirical, and statistical methods, the system behavior of the single planning entities is analyzed to predict the overall profitability a priori with a minimum of investment,- production,- and cycle time information. It is demonstrated that the necessary planning data, in terms of layout composition, robot velocities, and cycle times, can be frontloaded to the project’s beginning with a reverse engineering approach. The net present value serves as the target figure, whose dependency on the human-robot interaction grade can be illustrated in an advantageousness diagram for the individual technical alternatives. Consequently, sound economic decisions can be made on a quantitative basis.:1. Introduction 25 1.1 Research Domain 25 1.2 Research Niche 26 1.3 Research Structure 28 2. State of the Art and Research 31 2.1 Turning Machines and Machine Tending 31 2.1.1 Tooling Machine Market Trends and Machine Tending Systems 31 2.1.2 Workpiece System 34 2.1.3 Machine System 36 2.1.4 Logistics System 39 2.1.5 Handling System 41 2.2 Robotics 43 2.2.1 Robot Installation Development and Application Fields 43 2.2.2 Fenceless Industrial and Collaborative Robots 48 2.2.3 Robot Grippers 55 2.3 Planning and Evaluation Methods 56 2.3.1 Planning of General and Manual Workstations 56 2.3.2 Cell Planning for Fully Automated and Hybrid Robot Systems 59 2.3.3 Robot Safety Planning 61 2.3.4 Economic Evaluation Methods 70 2.4 Synthesis - State of the Art and Research 71 3. Solution Approach 77 3.1 Need for Research and General Solution Approach 77 3.2 Use Case Delineation and Planning Focus 80 3.3 Economic Module – Solution Approach 86 3.4 Gripper Feasibility Module – Solution Approach 89 3.5 Rough Layout Discretization Model – Solution Approach 94 3.6 Cycle Time Estimation Module – Solution Approach 97 3.7 Collaborative Speed Estimation Module – Solution Approach 103 3.7.1 General Approach 103 3.7.2 Case 1: Quasi-static Contact with Hand 107 3.7.3 Case 2: Transient Contact with Hand 109 3.7.4 Case 3: Transient Contact with Shoulder 111 3.8 Synthesis – Solution Approach 114 4. Module Development 117 4.1 Economic Module – Module Development 117 4.1.1 General Approach 117 4.1.2 Calculation Scheme for Manual Operation 117 4.1.3 Calculation Scheme for Collaborative Robots 118 4.1.4 Calculation Scheme for Industrial Robots 120 4.2 Gripper Feasibility Module – Module Development 121 4.3 Rough Layout Discretization Module – Module Development 122 4.3.1 General Approach 122 4.3.2 Two-Dimensional Layout Pattern 123 4.3.3 Three-Dimensional Layout Pattern 125 4.4 Cycle Time Estimation Module – Module Development 126 4.4.1 General Approach 126 4.4.2 Reachability Study 127 4.4.3 Simulation Results 128 4.5 Collaborative Speed Estimation Module – Module Development 135 4.5.1 General Approach 135 4.5.2 Case 1: Quasi-static Contact with Hand 135 4.5.3 Case 2: Transient Contact with Hand 143 4.5.4 Case 3: Transient Contact with Shoulder 145 4.6 Synthesis – Module Development 149 5. Practical Verification 155 5.1 Use Case Overview 155 5.2 Gripper Feasibility 155 5.3 Layout Discretization 156 5.4 Collaborative Speed Estimation 157 5.5 Cycle Time Estimation 158 5.6 Economic Evaluation 160 5.7 Synthesis – Practical Verification 161 6. Results and Conclusions 165 6.1 Scientific Findings and Results 165 6.2 Critical Appraisal and Outlook 17

Digestat fra biogassproduksjon som substrat og vektor for introduksjon av N2O-respirerende bakterier til landbuksjord

Anthropogenic nitrous oxide (N2O) emissions are largely driven by the input of N-based fertilizers in agriculture. N2O emissions from agricultural soils in Europe are estimated to 0.51 Tg annually (Fig. I), which sums to 48 % of total European N2O emissions and 35 % of the climate forcing from European agriculture. Yet, N2O emission mitigation from agriculture is still hampered by a lack of implemented abatement options. Whilst several biogeochemical reactions may release N2O (Fig. I) the enzyme nitrous oxide reductase (Nos) is the only known enzyme to reduce nitrous oxide. Nos is expressed in denitrifying and non-denitrifying prokaryotes and catalyzes the reduction of N2O to N2. The complete denitrification pathway is the stepwise reduction NO3- → NO2- → NO → N2O → N2, catalyzed by the enzymes Nar/Nap, Nir, Nor, and Nos that are encoded by the genes nar/nap, nirK/nirS, nor, and nosZ, respectively (Fig. I). A significant proportion of the denitrifying community in soils have truncated denitrification pathways, i.e. lacking one to three of the genes encoding the enzymes in the stepwise reduction of NO3- to N2. The consequence of such modularity is that organisms lacking nosZ are net N2O emitters, while organisms with nosZ only are net sinks for N2O. However, organisms equipped with a complete denitrification pathway can also be strong sinks or sources of N2O depending on their regulatory biology. N2O emissions from soils make up a substantial fraction of the climate forcing from food production and mitigation beyond that achieved by “good management practices” are needed if we are to limit global warming by 2 °C, as set in the Paris Agreement. One approach for reducing N2O emissions is to modify the soil microbiome, increasing the proportion of N2O-respiring bacteria (NRB) resulting in reduced N2O emissions. This would, however, be costly and impractical as a standalone operation. As an element towards a low-carbon circular economy, the volume of organic wastes channeled through AD is expected to increase in the coming decades. This presents a unique possibility for mitigation of N2O emissions as the residues of biogas production, digestates, destined as bio-fertilizers in agriculture, could be enriched with N2O-respiring bacteria before soil fertilization. Thus, providing a cost-efficient N2O mitigation measure (Fig. I). Here we demonstrate the use of biogas digestates from anaerobic digestion (AD) as a widely available, low-cost vector for NRB to agricultural soils. A primary task was to search for suitable organisms that 1) could grow to high cell densities in digestate and 2) would act as net N2O sinks in soil. To achieve this, enrichment culturing under anaerobic conditions with N2O as the sole electron acceptor was used. The enrichment cultures were monitored both by measuring the gas kinetics and by inspecting the composition of the microbiota by genomics and proteomics. Based on genomic information and targeted isolation, we obtained axenic cultures of the organisms that became dominant in the enrichment cultures. As a first approach, we enriched indigenous N2O-respiring bacteria in anaerobically digested sewage sludge (digestate) by anoxic incubation with N2O. The gas kinetics predicted that N2O-respiring organisms grew to high cell densities, which was confirmed by metagenomic and metaproteomic (omics-) analyses of the enriched digestate. The omics demonstrated dominance of organisms equipped with the nosZ clade II (coding for N2O-reductase), but also with the genes for the preceding steps of the denitrification pathway. Three digestate-derived N2O-reducing bacteria were isolated, of which one (Azonexus sp.) matched the recovered Metagenome-Assembled Genome (MAG) of the dominant N2O reducer with an average nucleotide identity (ANI) of 98.2%. This MAG also demonstrated a high complement of Nos in the enrichment as quantified by metaproteomics. Gas kinetics and meta-omics indicated that the anaerobic consortium of the digestate remained active during anaerobic incubation with N2O and that N2O-respiring bacteria grew by harvesting fermentation intermediates. The latter was supported by screening carbon catabolism profiles of the isolated organisms. The isolated Azonexus sp. demonstrated regulatory traits that would predict the organism to be a strong N2O sink, and it reduced immediate N2O emissions from digestate-amended soils. However, the Azonexus sp. was probably not an ideal N2O-respiring inoculant in soil because it was equipped with a full-fledged denitrification pathway and because its capacity to utilize soil carbon was limited. The importance of an active methanogenic community throughout the enrichments, providing fermentation intermediates as a carbon source for the N2O-respiring organisms, would predict a selective advantage for organisms with a streamlined (narrow) catabolic capacity, which was the case for the Azonexus sp.. It was evident that we needed to refine our search, to find organisms with a broader catabolic repertoire. A new procedure to obtain more ideal isolates was designed, involving a deliberate enrichment of N2O-respiring organisms with the characteristics of strong growth both in digestate and soil. We thought this could be achieved by “dual enrichment culturing”, i.e. a sequence of enrichment cultures where a fraction of a batch enrichment was passaged to the next batch, alternating between sterile soil and sterile digestate as substrate. Our point of departure was to model this approach, using a simple logistic model for the competition for a common substrate, between three distinctive groups; 1: Organisms with a competitive advantage in digestate (digestate specialists), 2: Organisms with a competitive advantage in soil (soil specialists), and 3: organisms capable of sustaining growth in both environments (generalists). The modelling revealed that generalists could indeed become dominant within a limited number of batch cultures, depending on their competitive edge vis a vis the specialists. Based on this we realized a dual enrichment experiment, using the microbiota of wastewater digestate and soil as initial inocula, sterile digestate and sterile soil as substrate, and monitored the gas kinetics and the community composition (by 16S rDNA amplicon sequencing) throughout seven consecutive enrichment cultures. The gas kinetics corroborated the model’s prediction of a gradual enrichment of organisms that grew both in soil and digestate, and the generalists that became dominant were identified as a limited number of Operational Taxonomic Units (OTUs, based on 16S rDNA sequencing). OTUs that became dominant circumscribed isolates obtained from the enrichment cultures. These OTUs also portrayed the targeted generalist as predicted by the modelling. Most isolates obtained had traits of strong N2O sinks, of which a dominating Cloacibacterium sp., carrying Nos (Clade II) as the sole N-reductase, significantly reduced N2O emissions in digestate amended soils of both neutral and acidic pH. A full-fledged denitrifying Pseudomonas sp. was able to persist in the soil for at least one month whereby significant N2O emissions reduction was obtained upon a fertilization event. Genome analysis of the isolated organisms shed some light as to why these organisms had a competitive advantage in both soil and digestate. Although the ideal isolate is yet to be found, we’ve opened an avenue to a concept that, within the expected expansion of AD, could be scaled to secure a substantial reduction in N2O emissions.Menneskeskapte utslipp av drivhusgassen lystgass (N2O) skyldes i stor grad tilførsel av nitrogenholdig gjødsel til landbruksjord. N2O-utslipp fra landbruksjord i Europa er estimert til 0,51 Tg årlig (Fig. I), som utgjør om lag 48% av de totale utslippene av N2O, som igjen representerer 35 % av det totale klimagassfotavtrykket fra europeisk landbruk. Begrensning av disse utslippene har vært utfordrende grunnet mangel på implementerte metoder og teknologier som effektivt reduserer lystgassutslippet fra landbruksjord. Flere biogeokjemiske reaksjoner kan frigjøre N2O (Fig. I), men enzymet lystgassreduktase (Nos) er det eneste kjente enzymet som reduserer N2O til N2. Nos uttrykkes av denitrifiserende prokaryoter og katalyserer reduksjonen av N2O til N2. Denitrifiserende prokaryoter katalyserer den trinnvise reduksjon av NO3- → NO2- → NO → N2O → N2, som katalyseres av enzymene Nar/Nap, Nir, Nor og Nos som er kodet av genene nar/nap, nir, nor og nosZ (Fig. I). Men, en betydelig andel av det denitrifiserende mikrobesamfunnet i jord er trunkert, dvs. en andel av denitrifikantene mangler ett til tre av genene som koder enzymene involvert i reduksjonen av NO3- til N2. En organisme som kun mangler nosZ vil produsere N2O. I motsatt tilfelle vil en organisme som kun er utstyrt med nosZ bare evne å redusere N2O. Organismer utstyrt med et komplett sett av gener for en fullstendig denitrifikasjon kan være både sterke og svake N2O-reduktanter. Dette bestemmes av deres regulatoriske biologi. N2O-utslipp fra jord utgjør en betydelig mengde av det totale klimafotavtrykket fra matproduksjon og en reduksjon av dette utslippet er nødvendig om vi skal nå de målene som er satt i Parisavtalen og begrense global oppvarming til 2 °C. En mulighet for å redusere N2O-utslipp er å modifisere jordmikrobiomet ved å øke andelen N2O-respirerende bakterier (NRB) – noe som vil redusere utslippene av N2O. Men, som ett frittstående tiltak vil en storskala modifisering av mikrobiologien i jordsmonnet være svært ressurskrevende. Som et ledd i overgangen til en lav-karbon sirkulærøkonomi forventes anaerob utråtning (AD) å øke i omfang og rekkevidde de neste årene. Denne utviklingen skaper en unik mulighet for å redusere N2O-utslipp dersom digestater, restproduktet fra AD, som brukes som organisk gjødsel i landbruket, kan anrikes med N2O-reduserende bakterier før disse digestatene benyttes som gjødsel (Fig. I). Her demonstrerer vi at lett tilgjengelige digestater kan benyttes som vekstsubstrat og en vektor for å overføre NRB til jord. En slik modifikasjon være et svært kostnadseffektivt N2O-reduserende tiltak. Det primære målet i denne avhandlingen var å lete etter egnede organismer som 1) kan gro til høy celletetthet i digestater, og 2) redusere N2O-utslipp fra jord. For å oppnå dette ble anrikninger av slike organismer ved bruk av N2O som eneste elektronakseptor gjennomført. Anrikningskulturene ble monitorert ved å måle gasskinetikk og ved overvåking av samfunnsprofiler og bakteriell populasjonsdynamikk ved bruk av DNA- og proteomanalyser. Med basis i den genetiske informasjonen var målet å isolere dominerende organismer fra anrikningskulturene. Som en første tilnærming anriket vi N2O-reduserende bakterier som er naturlig tilstedeværende i digestat i anoksiske inkubasjoner hvor N2O ble tilsatt som eneste elektronakseptor. Gasskinetikk predikerte at NRB vokste til høye celletettheter under inkubasjonen, som ble bekreftet av metagenom- og metaproteomanalyser av det anrikede digestatet. Meta-omikk analysene viste at organismer utstyrt med nosZ Type II (genet for N2O-reduktase), men også med de øvrige genene for et komplett denitrifiseringsspor, dominerte anrikningen. Tre N2O-reduserende bakterier ble isolert hvorav det ene isolatet, en Azonexus sp., samsvarte med et gjenvunnet Dechloromonas-beslektet metagenom som dominerte anrikningen med en aminosyreidentitet på 98,2% delt med det dominerende metagenomet. Metaproteomikk viste at dette metagenomet utrykte brorparten av Nos under anrikningen. Gasskinetikk og meta-omikk avslørte videre at det metanogene konsortiet i digestatet forblir aktivt også under den anaerobe inkubasjonen med N2O, og at dominerende bakterier med en anaerob respiratorisk metabolisme sannsynligvis vokste ved å høste fermenteringsmellomprodukter fra det metanogene samfunnet. Det sistnevnte ble støttet ved karbonkatabolismeprofiler for de isolerte organismene. Den isolerte Azonexus sp. demonstrerte regulatoriske egenskaper som ville forutsi at organismen var en sterk N2O-reduktant, og den reduserte N2O-utslipp fra jord gjødslet med Azonexus anriket digestat. Likevel så var anrikningsvinneren sannsynligvis ikke en ideell N2O-reduserende inokulant i jord fordi dens evne til å overleve i jord-miljøet sannsynligvis var begrenset. Betydningen av et aktivt metanogent bakteriesamfunn, som produsenter av karbonkilder for NRB igjennom anrikningene, gav sannsynligvis en selektiv fordel for organismer med en strømlinjeformet (smal) katabolsk kapasitet, som var tilfelle for Azonexus sp.. Det var tydelig at vi trengte å videreforedle anrikningsprosedyrene våre for å anrike kompetente organismer en bredere metabolsk fleksibilitet. En ny tilnærming for å oppnå mer ideelle isolater som evner å vokse i både jord og i digestat ble designet med utgangspunkt i å selektivt anrike organismer med disse egenskapene. Vi antok at slike organismer kunne anrikes ved en «dobbelt-anrikning»-prosedyre der miljøet ble vekslet mellom jord og digestat. Mao: En sekvens av batch-anrikningskulturer hvor en overfører en fraksjon av anrikningen til en ny batch og vekslet mellom jord og digestat som vekstsubstrat. Med dette utgangspunktet ble logistisk vekst, kun med konkurranse om tilgjengelig karbon, modellert for tre ulike bakteriegrupper; 1) Organismer med konkurransefortrinn i digestat (digestat-spesialister), 2) Organismer med konkurransefortrinn i jord (jordspesialister), og 3) organismer som er i stand til å opprettholde vekst/aktivitet i begge miljøer (generalister). Modelleringen avslørte at generalister teoretisk sett kunne anrikes ved å passere fraksjoner av disse anrikningene mellom digestat og jord, avhengig av generalistenes konkurransefortrinn relativt til spesialistene. Basert på denne modelleringen realiserte vi et nytt anrikningseksperiment med bruk av digestat og jord som initielt inokulum og sterilt digestat og jord som vekstsubstrat og lot populasjonene konkurrere om tilgjengelig karbon med tilsats av N2O. Monitorering av gasskinetikk og populasjonsdynamikk (ved 16S amplikonsekvensering) igjennom syv sammenhengende anrikninger viste en populasjonsutvikling slik predikert fra modelleringen: Gasskinetikken støttet modellprediksjonen om en gradvis ankrikning av organismer som vokste i jord og digestat, og 16S-analysen vist at et fåtall operasjonelle taksonomiske enheter (OTUer) dominerte anrikningen. Isolatene fra disse anrikningskulturene var omsluttet av en dominerende gruppe OTUer som portretterte vekstegenskaper igjennom hele anrikningsserien som representerte de ønskede generalistvinnerne. Ett av isolatene, en Cloacibacterium sp., hvis genom kun kodet for genet for Nos, dominerte anrikningene, og denne reduserte også N2O-utslipp i jord med lav pH. Et annet isolat, en Pseudomonas sp., demonstrert en mer langvarig N2O reduserende aktivitet i jord da aktiviteten var fremtredende selv 30 dager etter gjødsling. Genomanalyse av isolerte organismer kastet noe lys kring hvorfor disse organismer kunne ha et konkurransefortrinn i anrikningene. Selv om det ideelle isolatet ennå ikke er funnet, har vi åpnet en vei for et konsept som, i kontekst av den forventede utviklingen av AD, kan skaleres for å sikre betydelig reduksjon i N2O-utslipp.Vestfjorden Avløpsselskap (VEAS

RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach

The vision of the RoboEarth project is to design a knowledge-based system to provide web and cloud services that can transform a simple robot into an intelligent one. In this work, we describe the RoboEarth semantic mapping system. The semantic map is composed of: 1) an ontology to code the concepts and relations in maps and objects and 2) a SLAM map providing the scene geometry and the object locations with respect to the robot. We propose to ground the terminological knowledge in the robot perceptions by means of the SLAM map of objects. RoboEarth boosts mapping by providing: 1) a subdatabase of object models relevant for the task at hand, obtained by semantic reasoning, which improves recognition by reducing computation and the false positive rate; 2) the sharing of semantic maps between robots; and 3) software as a service to externalize in the cloud the more intensive mapping computations, while meeting the mandatory hard real time constraints of the robot. To demonstrate the RoboEarth cloud mapping system, we investigate two action recipes that embody semantic map building in a simple mobile robot. The first recipe enables semantic map building for a novel environment while exploiting available prior information about the environment. The second recipe searches for a novel object, with the efficiency boosted thanks to the reasoning on a semantically annotated map. Our experimental results demonstrate that, by using RoboEarth cloud services, a simple robot can reliably and efficiently build the semantic maps needed to perform its quotidian tasks. In addition, we show the synergetic relation of the SLAM map of objects that grounds the terminological knowledge coded in the ontology