Projecting Product-Aware Cues as Assembly Intentions for Human-Robot Collaboration

Collaborative environments between humans and robots are often characterized by simultaneous tasks carried out in close proximity. Recognizing robot intent in such circumstances can be crucial for operator safety and cannot be determined from robot motion alone. Projecting robot intentions on the product or the part the operator is collaborating on has the advantage that it is in the operator’s field of view and has the operator’s undivided attention. However, intention projection methods in literature use manual techniques for this purpose which can be prohibitively time consuming and unscalable to different part geometries. This problem is only more relevant in today’s manufacturing scenario that is characterized by part variety and volume. To this end, this study proposes (oriented) bounding boxes as a generalizable information construct for projecting assembly intentions that is capable of coping with different part geometries. The approach makes use of a digital thread framework for on-demand, run-time computation and retrieval of these bounding boxes from product CAD models and does so automatically without human intervention. A case-study with a real diesel engine assembly informs appreciable results and preliminary observations are discussed before presenting future directions for research.publishedVersionPeer reviewe

Using In-Browser Augmented Reality to Promote Knowledge-Based Engineering throughout the Product Life Cycle

While industry vastly undergoes digitalization, knowledge-based engineering becomes a powerful tool, helping enterprises to operate in context of shorter product life cycles and complex value chains. However, there are several challenges to be addressed in order to make knowledge-based engineering a common industry practice. There is a need for affordable tools, trained professionals, and extended use of outcomes of knowledge-based engineering processes beyond design phase of product life cycle. This article describes how web-based system delivering mobile augmented reality experience in browser may leverage results of product design process implemented with knowledge-based engineering tools in order to integrate information, and support its integrity and consistency for different stakeholders along the product life cycle. The approach relies on use of open standards and libraries in order to insure affordability and ease of integration, which is necessary for wider adoption of knowledge-based engineering among small and medium enterprises.acceptedVersionPeer reviewe

Deploying OWL ontologies for semantic mediation of mixed-reality interactions for human–robot collaborative assembly

For effective human–robot collaborative assembly, it is paramount to view both robots and humans as autonomous entities in that they can communicate, undertake different roles, and not be bound to pre-planned routines and task sequences. However, with very few exceptions, most of recent research assumes static pre-defined roles during collaboration with centralised architectures devoid of runtime communication that can influence task responsibility and execution. Furthermore, from an information system standpoint, they lack the self-organisation needed to cope with today’s manufacturing landscape that is characterised by product variants. Therefore, this study presents collaborative agents for manufacturing ontology (CAMO), which is an information model based on description logic that maintains a self-organising team network between collaborating human–robot multi-agent system (MAS). CAMO is implemented using the Web Ontology Language (OWL). It models popular notions of net systems and represents the agent, manufacturing, and interaction contexts that accommodate generalisability to different assemblies and agent capabilities. As a novel element, a dynamic consensus-driven collaboration based on parametric validation of semantic representations of agent capabilities via runtime dynamic communication is presented. CAMO is instantiated as agent beliefs in a framework that benefits from real-time dynamic communication with the assembly design environment and incorporates a mixed-reality environment for use by the operator. The employment of web technologies to project scalable notions of intentions via mixed reality is discussed for its novelty from a technology standpoint and as an intention projection mechanism. A case study with a real diesel engine assembly provides appreciable results and demonstrates the feasibility of CAMO and the framework.Peer reviewe

A Web-based Mixed Reality Interface Facilitating Explicit Agent-oriented Interactions for Human-Robot Collaboration

Communicating and recognizing intent is a crucial part of human-robot collaboration (HRC). It prevents competing and turn-taking behaviour that would otherwise lead to inefficient and unsafe collaborative activities. This study presents a novel approach towards enabling standards-based explicit bidirectional intent communication. The approach entails projecting a tailored web-based user interface upon the worktable shared between a human and robot agent. The interface has a close integration with an agent framework (JADE) that allows intent communication via mechanisms standardized by the IEEE Computer Society. The interaction model is discussed for its rationale and the possibilities it exposes as future work.acceptedVersionPeer reviewe

Supporting robotic welding of aluminium with a laser line scanner-based trigger definition method

Automation and the use of robots for welding operations is an important research topic. Being able to automate and, thus, save time for setting up and using robotic welding for complex, large-scale structures made of reflective materials, such as aluminium, will provide clear economic and competitive advantages. However, challenges coming from the ability to accurately detect and calibrate the robot for a given physical workpiece in addition to noises, such as the reflections, make it hard to develop and demonstrate a feasible automation solution. This paper proposes combining laser line scanning technology with CAD-based analysis of a workpiece geometry to support the identification of relevant elements of the workpiece in the physical world and thus support welding operations. An extendable trigger definition method is proposed to identify features of interest in a workpiece. The method can potentially support the execution of welding sequences, which in our case can be represented as a sequence of triggers that have to be observed and followed at the robot runtime to weld the workpiece together.acceptedVersio

Generation of rule-adhering robot programs for aluminium welding automatically from CAD

This paper presents a method to automatically generate robot welding programs from CAD to address the ever-constant demand for product customisation. Furthermore, to ensure that proper welding operations and structural integrity are met, the generated programs also consider the welding conditions and requirements. These welding conditions and requirements are defined by the weld direction and face relative to gravity and surrounding geometry, which has not been observed in the present research sphere. To achieve this, the approach leverages information that can be extracted from a topological analysis of tessellated geometry local to the weld joint in conjunction with available CAD API functions. Finally, an implementation of the method using Siemens NX and the Robotics Toolbox for Python is presented and tested on three geometrically different node configurations and a stiffener piece provided by industrial collaborators. In all, the proposed system was able to correctly generate programs adhering to allowed welding operations as long as a solution existed. For the more complex node configurations (which require reorientation when welded by humans), 32 weld path programs out of 42 were generated based on the given criteria. For the least complex node, a total of 20 out of 24 were generated with the same criteria. All 14 weld programs were generated for the stiffener representation.publishedVersio

Enabling the Digital Thread for Product Aware Human and Robot Collaboration - An Agent-oriented System Architecture

Customized product requirements are driving the need for variety oriented assemblies even in collaborative environments between humans and robots. This calls for the need for robots and humans to be intelligent in order to be aware of and adapt to different product needs. To address this, this study presents a novel approach and architecture to realize a digital thread that allows human and robot agents access to the product model at system run-time. The approach entails modelling a knowledge-based engineering (KBE) software as an agent which actively participates with collaborative agents via communication mechanisms standardized by the IEEE Computer Society. The architecture is described by four concurrent views and is discussed for its advantages and design rationale.acceptedVersionPeer reviewe

Product, process and resource model coupling for knowledge-driven assembly automation

: Accommodating frequent product changes in a short period of time is a challenging task due to limitations of the contemporary engineering approach to design, build and reconfigure automation systems. In particular, the growing quantity and diversity of manufacturing information, and the increasing need to exchange and reuse this information in an efficient way has become a bottleneck. To improve the engineering process, digital manufacturing and Product, Process and Resource (PPR) modelling are considered very promising to compress development time and engineering cost by enabling efficient design and reconfiguration of manufacturing resources. However, due to ineffective coupling of PPR data, design and reconfiguration of assembly systems are still challenging tasks due to the dependency on the knowledge and experience of engineers. This paper presents an approach for data models integration that can be employed for coupling the PPR domain models for matching the requirements of products for assembly automation. The approach presented in this paper can be used effectively to link data models from various engineering domains and engineering tools. For proof of concept, an example implementation of the approach for modelling and integration of PPR for a Festo test rig is presented as a case study

Smart textile waste collection system – Dynamic route optimization with IoT

Increasing textile production is associated with an environmental burden which can be decreased with an improved recycling system by digitalization. The collection of textiles is done with so-called curbside bins. Sensor technologies support dynamic-informed decisions during route planning, helping predict waste accumulation in bins, which is often irregular and difficult to predict. Therefore, dynamic route-optimization decreases the costs of textile collection and its environmental load. The existing research on the optimization of waste collection is not based on real-world data and is not carried out in the context of textile waste. The lack of real-world data can be attributed to the limited availability of tools for long-term data collection. Consequently, a system for data collection with flexible, low-cost, and open-source tools is developed. The viability and reliability of such tools are tested in practice to collect real-world data. This research demonstrates how smart bins solution for textile waste collection can be linked to a dynamic route-optimization system to improve overall system performance. The developed Arduino-based low-cost sensors collected actual data in Finnish outdoor conditions for over twelve months. The viability of the smart waste collection system was complemented with a case study evaluating the collection cost of the conventional and dynamic scheme of discarded textiles. The results of this study show how a sensor-enhanced dynamic collection system reduced the cost 7.4% compared with the conventional one. We demonstrate a time efficiency of −7.3% and that a reduction of 10.2% in CO2 emissions is achievable only considering the presented case study.publishedVersionPeer reviewe

Proteomic similarity of the Littorinid snails in the evolutionary context

Background The introduction of DNA-based molecular markers made a revolution in biological systematics. However, in cases of very recent divergence events, the neutral divergence may be too slow, and the analysis of adaptive part of the genome is more informative to reconstruct the recent evolutionary history of young species. The advantage of proteomics is its ability to reflect the biochemical machinery of life. It may help both to identify rapidly evolving genes and to interpret their functions. Methods Here we applied a comparative gel-based proteomic analysis to several species from the gastropod family Littorinidae. Proteomes were clustered to assess differences related to species, geographic location, sex and body part, using data on presence/absence of proteins in samples and data on protein occurrence frequency in samples of different species. Cluster support was assessed using multiscale bootstrap resampling and the stability of clustering—using cluster-wise index of cluster stability. Taxon-specific protein markers were derived using IndVal method. Proteomic trees were compared to consensus phylogenetic tree (based on neutral genetic markers) using estimates of the Robinson–Foulds distance, the Fowlkes–Mallows index and cophenetic correlation. Results Overall, the DNA-based phylogenetic tree and the proteomic similarity tree had consistent topologies. Further, we observed some interesting deviations of the proteomic littorinid tree from the neutral expectations. (1) There were signs of molecular parallelism in two Littoraria species that phylogenetically are quite distant, but live in similar habitats. (2) Proteome divergence was unexpectedly high between very closely related Littorina fabalis and L. obtusata, possibly reflecting their ecology-driven divergence. (3) Conservative house-keeping proteins were usually identified as markers for cryptic species groups (“saxatilis” and “obtusata” groups in the Littorina genus) and for genera (Littoraria and Echinolittorina species pairs), while metabolic enzymes and stress-related proteins (both potentially adaptively important) were often identified as markers supporting species branches. (4) In all five Littorina species British populations were separated from the European mainland populations, possibly reflecting their recent phylogeographic history. Altogether our study shows that proteomic data, when interpreted in the context of DNA-based phylogeny, can bring additional information on the evolutionary history of species