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Östlund, G., Rautell Lindstedt, P., Curuklu, B. & Blomberg, H. (2023). Developing welfare technology to increase children’s participation in child welfare assessments: an empirical case in Sweden. European Journal of Social Work
Åpne denne publikasjonen i ny fane eller vindu >>Developing welfare technology to increase children’s participation in child welfare assessments: an empirical case in Sweden
2023 (engelsk)Inngår i: European Journal of Social Work, ISSN 1369-1457, E-ISSN 1468-2664Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The purpose of the article is to describe and problematise the practice-initiated idea of developing a digital tool for children in child welfare investigations and whether and how this welfare technology is useful for social workers. The results include interview data and descriptions of the research process. The social workers are of the opinion that the digital application increases the possibilities for children’s participation in child investigations, even though their main focus is to create an alliance with the parents. During the research process the digital tool has developed from an empirical idea to a conversation tool and been tested with different user groups. However, the law on procurement limits the possibilities for data storage if the digital tool is to be used in the future. In sum, in order to develop child protection work further, more practice-based research needs to be conducted so that researchers can develop the practice’s ideas and identify the obstacles, opportunities, organisational conditions and development needs. The social workers in this study believe that the digital tool is useful for accessing children's perspectives and experiences, even though relational work with children is not their main task in child welfare investigations. 

sted, utgiver, år, opplag, sider
Routledge, 2023
Emneord
Child welfare assessments, children’s participation, digital tools, human-computer interaction, social work, article, child, child protection, child welfare, conversation, human, human computer interaction, information storage, interview, social worker, Sweden
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-63969 (URN)10.1080/13691457.2023.2243053 (DOI)001043187300001 ()2-s2.0-85166940233 (Scopus ID)
Tilgjengelig fra: 2023-08-16 Laget: 2023-08-16 Sist oppdatert: 2023-12-06bibliografisk kontrollert
Ameri, A., Miloradović, B., Curuklu, B., Papadopoulos, A., Ekström, M. & Dreo, J. (2023). Interplay of Human and AI Solvers on a Planning Problem. In: Conf. Proc. IEEE Int. Conf. Syst. Man Cybern.: . Paper presented at Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (pp. 3166-3173). Institute of Electrical and Electronics Engineers Inc.
Åpne denne publikasjonen i ny fane eller vindu >>Interplay of Human and AI Solvers on a Planning Problem
Vise andre…
2023 (engelsk)Inngår i: Conf. Proc. IEEE Int. Conf. Syst. Man Cybern., Institute of Electrical and Electronics Engineers Inc. , 2023, s. 3166-3173Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

With the rapidly growing use of Multi-Agent Systems (MASs), which can exponentially increase the system complexity, the problem of planning a mission for MASs became more intricate. In some MASs, human operators are still involved in various decision-making processes, including manual mission planning, which can be an ineffective approach for any non-trivial problem. Mission planning and re-planning can be represented as a combinatorial optimization problem. Computing a solution to these types of problems is notoriously difficult and not scalable, posing a challenge even to cutting-edge solvers. As time is usually considered an essential resource in MASs, automated solvers have a limited time to provide a solution. The downside of this approach is that it can take a substantial amount of time for the automated solver to provide a sub-optimal solution. In this work, we are interested in the interplay between a human operator and an automated solver and whether it is more efficient to let a human or an automated solver handle the planning and re-planning problems, or if the combination of the two is a better approach. We thus propose an experimental setup to evaluate the effect of having a human operator included in the mission planning and re-planning process. Our tests are performed on a series of instances with gradually increasing complexity and involve a group of human operators and a metaheuristic solver based on a genetic algorithm. We measure the effect of the interplay on both the quality and structure of the output solutions. Our results show that the best setup is to let the operator come up with a few solutions, before letting the solver improve them.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers Inc., 2023
Emneord
Human-AI Collaboration, Mixed Human-AI Planning, Multi-Agent Mission Planning
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-66283 (URN)10.1109/SMC53992.2023.10394024 (DOI)2-s2.0-85187278849 (Scopus ID)9798350337020 (ISBN)
Konferanse
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Merknad

Conference paper; Export Date: 20 March 2024; Cited By: 0; Correspondence Address: E. Afshin Ameri; Mälardalen University, Västerås, Sweden; email: afshinameri.e@mdu.se; B. Miloradović; Mälardalen University, Västerås, Sweden; email: branko.miloradovic@mdu.se; B. Çürüklü; Mälardalen University, Västerås, Sweden; email: baran.curuklu@mdu.se; A.V. Papadopoulos; Mälardalen University, Västerås, Sweden; email: alessandrov.papadopoulos@mdu.se; M. Ekström; Mälardalen University, Västerås, Sweden; email: mikael.ekstrom@mdu.se; CODEN: PICYE

Tilgjengelig fra: 2024-03-20 Laget: 2024-03-20 Sist oppdatert: 2024-03-20bibliografisk kontrollert
Miloradović, B., Curuklu, B., Ekström, M. & Papadopoulos, A. (2023). Optimizing Parallel Task Execution for Multi-Agent Mission Planning. IEEE Access, 11, 24367-24381
Åpne denne publikasjonen i ny fane eller vindu >>Optimizing Parallel Task Execution for Multi-Agent Mission Planning
2023 (engelsk)Inngår i: IEEE Access, E-ISSN 2169-3536, Vol. 11, s. 24367-24381Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Multi-agent systems have received a tremendous amount of attention in many areas of research and industry, especially in robotics and computer science. With the increased number of agents in missions, the problem of allocation of tasks to agents arose, and it is one of the most fundamental classes of problems in robotics, formally known as the Multi-Robot Task Allocation (MRTA) problem. MRTA encapsulates numerous problem dimensions, and it aims at providing formulations and solutions to various problem configurations, i.e., complex multi-agent missions. One dimension of the MRTA problem has not caught much of the research attention. In particular, problem configurations including Multi-Task (MT) robots have been neglected. However, the increase in computational power, in robotic systems, has allowed the utilization of parallel task execution. This in turn had the benefit of allowing the creation of more complex robotic missions; however, it came at the cost of increased problem complexity. Our contribution to the aforementioned domain can be grouped into three categories. First, we model the problem using two different approaches, Integer Linear Programming and Constraint Programming. With these models, we aim at filling the gap in the literature related to the formal definition of MT robot problem configuration. Second, we introduce the distinction between physical and virtual tasks and their mutual relationship in terms of parallel task execution. This distinction allows the modeling of a wider range of missions while exploiting possible parallel task execution. Finally, we provide a comprehensive performance analysis of both models, by implementing and validating them in CPLEX and CP Optimizer on the set of problems. Each problem consists of the same set of test instances gradually increasing in complexity, while the percentage of virtual tasks in each problem is different. The analysis of the results includes exploration of the scalability of both models and solvers, the effect of virtual tasks on the solvers' performance, and overall solution quality.

sted, utgiver, år, opplag, sider
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023
Emneord
Task analysis, Robots, Planning, Taxonomy, Resource management, Complexity theory, Analytical models, Multi-agent mission planning, multi-robot task allocation, parallel task execution, integer linear programming, constraint programming
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-62204 (URN)10.1109/ACCESS.2023.3254900 (DOI)000953721300001 ()2-s2.0-85149859205 (Scopus ID)
Tilgjengelig fra: 2023-04-12 Laget: 2023-04-12 Sist oppdatert: 2023-04-12bibliografisk kontrollert
Merz, M., Pedro, D., Skliros, V., Bergenhem, C., Himanka, M., Houge, T., . . . Johansen, G. (2022). Autonomous UAS-Based Agriculture Applications: General Overview and Relevant European Case Studies. DRONES, 6(5), Article ID 128.
Åpne denne publikasjonen i ny fane eller vindu >>Autonomous UAS-Based Agriculture Applications: General Overview and Relevant European Case Studies
Vise andre…
2022 (engelsk)Inngår i: DRONES, ISSN 2504-446X, Vol. 6, nr 5, artikkel-id 128Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.

sted, utgiver, år, opplag, sider
MDPI, 2022
Emneord
autonomy, unmanned aircraft system, agriculture, regulations
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-59054 (URN)10.3390/drones6050128 (DOI)000802556100001 ()2-s2.0-85130701173 (Scopus ID)
Tilgjengelig fra: 2022-06-15 Laget: 2022-06-15 Sist oppdatert: 2022-08-29bibliografisk kontrollert
Blomberg, H., Östlund, G., Lindstedt Rautell, P. & Curuklu, B. (2022). Children helping to co-construct a digital tool that is designed to increase children’s participation in child welfare investigations in Sweden.. Qualitative Social Work, 21(2), 367-392
Åpne denne publikasjonen i ny fane eller vindu >>Children helping to co-construct a digital tool that is designed to increase children’s participation in child welfare investigations in Sweden.
2022 (engelsk)Inngår i: Qualitative Social Work, ISSN 1473-3250, E-ISSN 1741-3117, Vol. 21, nr 2, s. 367-392Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

How do children (aged 6-12 years) understand and make use of a digital tool that is under development? This article builds on an ongoing interdisciplinary research project in which children, social workers (the inventers of this social innovation) and researchers together develop an interactive digital tool (application) to strengthen children's participation during the planning and process of welfare assessments. Departing from social constructionism, and using a discursive narrative approach with visual ethnography, the aim of the article is to display how the children co-construct the application and contribute with "stories of life situations" by drawing themselves as characters and the places they frequent. The findings show that the children improved the application by suggesting more affordances so that they could better create themselves/others, by discovering bugs, and by showing how it could appeal to children of various ages. The application helped the children to start communicating and bonding when creating themselves in detail, drawing places/characters and describing events associated with them, and sharing small life stories. The application can help children and social workers to connect and facilitate children's participation by allowing them to focus on their own perspectives when drawing and sharing stories.

HSV kategori
Forskningsprogram
socialt arbete
Identifikatorer
urn:nbn:se:mdh:diva-53277 (URN)10.1177/1473325021990864 (DOI)000618471700001 ()2-s2.0-85100548381 (Scopus ID)
Forskningsfinansiär
Forte, Swedish Research Council for Health, Working Life and Welfare, 2018-01319
Tilgjengelig fra: 2021-01-31 Laget: 2021-01-31 Sist oppdatert: 2022-06-13bibliografisk kontrollert
Trinh, L., Ekström, M. & Curuklu, B. (2022). Dependable Navigation for Multiple Autonomous Robots with Petri Nets Based Congestion Control and Dynamic Obstacle Avoidance. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 104(4), Article ID 69.
Åpne denne publikasjonen i ny fane eller vindu >>Dependable Navigation for Multiple Autonomous Robots with Petri Nets Based Congestion Control and Dynamic Obstacle Avoidance
2022 (engelsk)Inngår i: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, ISSN 0921-0296, Vol. 104, nr 4, artikkel-id 69Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this paper, a novel path planning algorithm for multiple robots using congestion analysis and control is presented. The algorithm ensures a safe path planning solution by avoiding collisions among robots as well as among robots and humans. For each robot, alternative paths to the goal are realised. By analysing the travelling time of robots on different paths using Petri Nets, the optimal configuration of paths is selected. The prime objective is to avoid congestion when routing many robots into a narrow area. The movements of robots are controlled at every intersection by organising a one-by-one passing of the robots. Controls are available for the robots which are able to communicate and share information with each other. To avoid collision with humans and other moving objects (i.e. robots), a dipole field integrated with a dynamic window approach is developed. By considering the velocity and direction of the dynamic obstacles as sources of a virtual magnetic dipole moment, the dipole-dipole interaction between different moving objects will generate repulsive forces proportional to the velocity to prevent collisions. The whole system is presented on the widely used platform Robot Operating System (ROS) so that its implementation is extendable to real robots. Analysis and experiments are demonstrated with extensive simulations to evaluate the effectiveness of the proposed approach.

Emneord
Dependable path planning, Dipole field, Obstacle avoidance, Congestion control
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-56589 (URN)10.1007/s10846-022-01589-1 (DOI)000777399100001 ()2-s2.0-85127723096 (Scopus ID)
Tilgjengelig fra: 2021-11-23 Laget: 2021-11-23 Sist oppdatert: 2022-11-02bibliografisk kontrollert
Miloradović, B., Curuklu, B., Ekström, M. & Papadopoulos, A. (2022). GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications. IEEE Transactions on Cybernetics, 52(10), 10627-10638
Åpne denne publikasjonen i ny fane eller vindu >>GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications
2022 (engelsk)Inngår i: IEEE Transactions on Cybernetics, ISSN 2168-2267, E-ISSN 2168-2275, Vol. 52, nr 10, s. 10627-10638Artikkel i tidsskrift (Fagfellevurdert) Epub ahead of print
Abstract [en]

The use of multiagent systems (MASs) in real-world applications keeps increasing, and diffuses into new domains, thanks to technological advances, increased acceptance, and demanding productivity requirements. Being able to automate the generation of mission plans for MASs is critical for managing complex missions in realistic settings. In addition, finding the right level of abstraction to represent any generic MAS mission is important for being able to provide general solution to the automated planning problem. In this article, we show how a mission for heterogeneous MASs can be cast as an extension of the traveling salesperson problem (TSP), and we propose a mixed-integer linear programming formulation. In order to solve this problem, a genetic mission planner (GMP), with a local plan refinement algorithm, is proposed. In addition, the comparative evaluation of CPLEX and GMP is presented in terms of timing and optimality of the obtained solutions. The algorithms are benchmarked on a proposed set of different problem instances. The results show that, in the presence of timing constraints, GMP outperforms CPLEX in the majority of test instances.

Emneord
Extended Colored Traveling Salesperson Problem (ECTSP)Genetic Algorithm (GA)Multirobot Mission PlanningMultirobot Systems
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-54306 (URN)10.1109/TCYB.2021.3070913 (DOI)000733455200001 ()33983890 (PubMedID)2-s2.0-85105850900 (Scopus ID)
Prosjekter
Aggregate Farming in the CloudFIESTA - Federated Choreography of an Integrated Embedded Systems Software Architecture
Tilgjengelig fra: 2021-06-01 Laget: 2021-06-01 Sist oppdatert: 2022-11-17bibliografisk kontrollert
Östlund, G., Blomberg, H., Rautell Lindstedt, P. & Curuklu, B. (2021). DIG Child ett digitalt metodverktyg för ökad delaktighet.. In: : . Paper presented at Barnrättsdagarna, Stiftelsen Allmänna Barnhuset, 14-15 september, Digital nationell konferens.
Åpne denne publikasjonen i ny fane eller vindu >>DIG Child ett digitalt metodverktyg för ökad delaktighet.
2021 (svensk)Konferansepaper, Oral presentation with published abstract (Annet vitenskapelig)
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-56187 (URN)
Konferanse
Barnrättsdagarna, Stiftelsen Allmänna Barnhuset, 14-15 september, Digital nationell konferens
Forskningsfinansiär
Forte, Swedish Research Council for Health, Working Life and Welfare, 2018-01319
Tilgjengelig fra: 2021-10-13 Laget: 2021-10-13 Sist oppdatert: 2021-12-14bibliografisk kontrollert
Miloradović, B., Curuklu, B., Ekström, M. & Papadopoulos, A. (2021). Exploiting Parallelism in Multi-Task Robot Allocation Problems. In: 2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC): . Paper presented at International Conference on Autonomous Robot Systems and Competitions ICARSC, 28 Apr 2021, Santa Maria de Feria, Portugal (pp. 197-202).
Åpne denne publikasjonen i ny fane eller vindu >>Exploiting Parallelism in Multi-Task Robot Allocation Problems
2021 (engelsk)Inngår i: 2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), 2021, s. 197-202Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Multi-Agent Systems (MASs) have been widely adopted in robotics, as a means to solve complex missions by subdividing them into smaller tasks. In such a context, Multi-Robot Task Allocation (MRTA) has been a relevant research area, with the main aim of providing formulations and solutions to different mission configurations, in order to optimize the planning and the execution of complex missions utilizing multiple robots. In recent years, robotic systems have become more powerful thanks to the adoption of novel computing platforms, enabling an increased level of parallelism, in terms of sensing, actuation, and computation. As a result, more complex missions can be achieved, at the cost of an increased complexity for the optimization of the mission planning. In this paper, we first introduce the distinction between physical and virtual tasks of the robots, and their relation in terms of parallel execution. Therefore, we propose a mathematical formalization of the mission planning problem for Multi-Task (MT) robots, in the presence of tasks that require only a Single-Robot (SR) to complete, and in the presence of Time-Extended Assignments (TAs). The problem is modeled with a Mixed-Integer Linear Programming (MILP) formulation, with the objective of minimizing the total makespan of the mission, exploiting the potential (physical and virtual) parallelism of the robots. The model is validated over some representative scenarios, and their respective solutions are obtained with the CPLEX optimization tool, showing the generality of the proposed formulation.

Emneord
Multi-Robot Task Allocation, Parallel Task Execution, Mixed-Integer Linear Programming
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-54299 (URN)10.1109/ICARSC52212.2021.9429814 (DOI)000679389400034 ()2-s2.0-85107149093 (Scopus ID)978-1-6654-3198-9 (ISBN)
Konferanse
International Conference on Autonomous Robot Systems and Competitions ICARSC, 28 Apr 2021, Santa Maria de Feria, Portugal
Prosjekter
Aggregate Farming in the CloudFIESTA - Federated Choreography of an Integrated Embedded Systems Software Architecture
Tilgjengelig fra: 2021-06-01 Laget: 2021-06-01 Sist oppdatert: 2021-11-22bibliografisk kontrollert
Miloradović, B., Curuklu, B., Ekström, M. & Papadopoulos, A. (2021). Optimizing Parallel Task Execution for Multi-Agent Mission Planning.
Åpne denne publikasjonen i ny fane eller vindu >>Optimizing Parallel Task Execution for Multi-Agent Mission Planning
2021 (engelsk)Manuskript (preprint) (Annet vitenskapelig)
Abstract [en]

Multi-Agent Systems have received a tremendous amount of attention in many areas of research and industry, especially in robotics and computer science. With the increased number of agents in missions, the problem of allocation of tasks to agents arose, and it is one of the most fundamental classes of problems in robotics, formally known as the Multi-Robot Task Allocation (MRTA) problem. MRTA encapsulates numerous problem dimensions, and it aims at providing formulations and solutions to various problem configurations, i.e., complex multi-robot missions.

One dimension of the MRTA problem has not caught much of the research attention. In particular, problem configurations including Multi-Task (MT) robots have been neglected. However, the increase in computational power, in robotic systems, has allowed the utilization of parallel task execution. This in turn had the benefit of allowing the creation of more complex robotic missions; however, it came at the cost of increased problem complexity. 

To overcome the aforementioned problem, we introduce the distinction between physical and virtual tasks and their mutual relationship in terms of parallel task execution. To fill in the gap in the literature related to MT robot problem configurations, we provide a formalization of the mission planning problem, using MT robots, in the form of Integer Linear Programming and Constraint Programming (CP), to minimize the mission makespan. The models are validated in CPLEX and CP Optimizer on the set of benchmarks. Moreover, we provide a comprehensive performance analysis of both solvers, exploring their scalability and solution quality.

Publisher
s. 32
Emneord
Multi-Robot Task Allocation, Parallel Task Execution, Integer Linear Programming
HSV kategori
Forskningsprogram
datavetenskap
Identifikatorer
urn:nbn:se:mdh:diva-56552 (URN)
Tilgjengelig fra: 2021-11-19 Laget: 2021-11-19 Sist oppdatert: 2021-11-22bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0002-5224-8302