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Sgorbissa, A., Papadopoulos, I., Papadopoulos, C., Saffiotti, A., Pandey, A. K., Merton, L., . . . Mastrolonardo, R. (2019). CARESSES: The Flower that Taught Robots about Culture. In: HRI '19: 2019 14TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION. Paper presented at 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2019), Daegu, South Korea, March 11-14, 2019 (pp. 371-371). IEEE, Article ID 8673086.
Open this publication in new window or tab >>CARESSES: The Flower that Taught Robots about Culture
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2019 (English)In: HRI '19: 2019 14TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, IEEE , 2019, p. 371-371, article id 8673086Conference paper, Published paper (Refereed)
Abstract [en]

The video describes the novel concept of "culturally competent robotics", which is the main focus of the project CARESSES (Culturally-Aware Robots and Environmental Sensor Systems for Elderly Support). CARESSES a multidisciplinary project whose goal is to design the first socially assistive robots that can adapt to the culture of the older people they are taking care of. Socially assistive robots are required to help the users in many ways including reminding them to take their medication, encouraging them to keep active, helping them keep in touch with family and friends. The video describes a new generation of robots that will perform their actions with attention to the older person's customs, cultural practices and individual preferences.

Place, publisher, year, edition, pages
IEEE, 2019
Series
ACM IEEE International Conference on Human-Robot Interaction, ISSN 2167-2121, E-ISSN 2167-2148
Keywords
Culturally competent robots, elderly care
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:oru:diva-74427 (URN)10.1109/HRI.2019.8673086 (DOI)000467295400053 ()2-s2.0-85064002082 (Scopus ID)978-1-5386-8555-6 (ISBN)
Conference
14th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2019), Daegu, South Korea, March 11-14, 2019
Available from: 2019-05-28 Created: 2019-05-28 Last updated: 2019-05-28Bibliographically approved
Mansouri, M., Lacerda, B., Hawes, N. & Pecora, F. (2019). Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints. In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19): . Paper presented at The 28th International Joint Conference on Artificial Intelligence (IJCAI19), August 10-16, Macao, China (pp. 478-484).
Open this publication in new window or tab >>Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints
2019 (English)In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 2019, p. 478-484Conference paper, Published paper (Refereed)
Abstract [en]

We present a novel modelling and planning approach for multi-robot systems under uncertain travel times. The approach uses generalised stochastic Petri nets (GSPNs) to model desired team behaviour, and allows to specify safety constraints and rewards. The GSPN is interpreted as a Markov decision process (MDP) for which we can generate policies that optimise the requirements. This representation is more compact than the equivalent multi-agent MDP, allowing us to scale better. Furthermore, it naturally allows for asynchronous execution of the generated policies across the robots, yielding smoother team behaviour. We also describe how the integration of the GSPN with a lower-level team controller allows for accurate expectations on team performance. We evaluate our approach on an industrial scenario, showing that it outperforms hand-crafted policies used in current practice.

Keywords
Multi-agent planning, robot planning, planning with uncertainy
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-75820 (URN)
Conference
The 28th International Joint Conference on Artificial Intelligence (IJCAI19), August 10-16, Macao, China
Available from: 2019-08-18 Created: 2019-08-18 Last updated: 2019-08-19
Mannucci, A., Pallottino, L. & Pecora, F. (2019). Provably Safe Multi-Robot Coordination With Unreliable Communication. IEEE Robotics and Automation Letters, 4(4), 3232-3239
Open this publication in new window or tab >>Provably Safe Multi-Robot Coordination With Unreliable Communication
2019 (English)In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, no 4, p. 3232-3239Article in journal (Refereed) Published
Abstract [en]

Coordination is a core problem in multi-robot systems, since it is a key to ensure safety and efficiency. Both centralized and decentralized solutions have been proposed, however, most assume perfect communication. This letter proposes a centralized method that removes this assumption, and is suitable for fleets of robots driven by generic second-order dynamics. We formally prove that: first, safety is guaranteed if communication errors are limited to delays; and second, the probability of unsafety is bounded by a function of the channel model in networks with packet loss. The approach exploits knowledge of the network's non-idealities to ensure the best possible performance of the fleet. The method is validated via several experiments with simulated robots.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
Keywords
Multi-robot systems, planning, scheduling and coordination, formal methods in robotics and automation
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:oru:diva-75700 (URN)10.1109/LRA.2019.2924849 (DOI)000476791300016 ()2-s2.0-85069779068 (Scopus ID)
Funder
EU, Horizon 2020, 732737
Note

Funding Agency:

Swedish Knowledge Foundation (KKS) under the Semantic Robots research profile

Available from: 2019-08-14 Created: 2019-08-14 Last updated: 2019-08-14Bibliographically approved
Grosinger, J., Pecora, F. & Saffiotti, A. (2019). Robots that Maintain Equilibrium: Proactivity by Reasoning About User Intentions and Preferences. Pattern Recognition Letters, 118, 85-93
Open this publication in new window or tab >>Robots that Maintain Equilibrium: Proactivity by Reasoning About User Intentions and Preferences
2019 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 118, p. 85-93Article in journal (Refereed) Published
Abstract [en]

Robots need to exhibit proactive behavior if they are to be accepted in human-centered environments. A proactive robot must reason about the actions it can perform, the state of the environment, the state and the intentions of its users, and what the users deem desirable. This paper proposes a computational framework for proactive robot behavior that formalizes the above ingredients. The framework is grounded on the notion of Equilibrium Maintenance: current and future states are continuously evaluated to identify opportunities for acting that steer the system into more desirable states. We show that this process leads a robot to proactively generate its own goals and enact them, and that the obtained behavior depends on a model of user intentions, preferences, and the temporal horizon used in prediction. A number of examples show that our framework accounts for even slight variations in user preference models and perceived user intentions. We also show how the level of informedness of the system is easily customizable.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Robot proactivity, Equilibrium maintenance, Goal reasoning, Fuzzy models
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-65667 (URN)10.1016/j.patrec.2018.05.014 (DOI)000457976400010 ()2-s2.0-85048078578 (Scopus ID)
Funder
Swedish Research Council, PGR00193
Note

Funding Agency:

Semantic Robots Research Profile (Swedish Knowledge Foundation)

Available from: 2018-03-12 Created: 2018-03-12 Last updated: 2019-02-19Bibliographically approved
Pecora, F., Mansouri, M., Hawes, N. & Kunze, L. (2019). Special Issue on Reintegrating Artificial Intelligence and Robotics. Künstliche Intelligenz, 33(4), 315-317
Open this publication in new window or tab >>Special Issue on Reintegrating Artificial Intelligence and Robotics
2019 (English)In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 33, no 4, p. 315-317Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2019
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-77894 (URN)10.1007/s13218-019-00625-x (DOI)
Available from: 2019-11-14 Created: 2019-11-14 Last updated: 2019-11-15Bibliographically approved
Pecora, F., Andreasson, H., Mansouri, M. & Petkov, V. (2018). A Loosely-Coupled Approach for Multi-Robot Coordination, Motion Planning and Control, ICAPS. In: Mathijs de Weerdt, Sven Koenig, Gabriele Röger, Matthijs Spaan (Ed.), Proceedings of the International Conference on Automated Planning and Scheduling: . Paper presented at International Conference on Automated Planning and Scheduling (ICAPS 2018), Delft, The Netherland, June 24-29, 2018 (pp. 485-493). Delft, The Netherlands: AAAI Press, 2018-June, Article ID 139850.
Open this publication in new window or tab >>A Loosely-Coupled Approach for Multi-Robot Coordination, Motion Planning and Control, ICAPS
2018 (English)In: Proceedings of the International Conference on Automated Planning and Scheduling / [ed] Mathijs de Weerdt, Sven Koenig, Gabriele Röger, Matthijs Spaan, Delft, The Netherlands: AAAI Press, 2018, Vol. 2018-June, p. 485-493, article id 139850Conference paper, Published paper (Refereed)
Abstract [en]

Deploying fleets of autonomous robots in real-world applications requires addressing three problems: motion planning, coordination, and control. Application-specific features of the environment and robots often narrow down the possible motion planning and control methods that can be used. This paper proposes a lightweight coordination method that implements a high-level controller for a fleet of potentially heterogeneous robots. Very few assumptions are made on robot controllers, which are required only to be able to accept set point updates and to report their current state. The approach can be used with any motion planning method for computing kinematically-feasible paths. Coordination uses heuristics to update priorities while robots are in motion, and a simple model of robot dynamics to guarantee dynamic feasibility. The approach avoids a priori discretization of the environment or of robot paths, allowing robots to “follow each other” through critical sections. We validate the method formally and experimentally with different motion planners and robot controllers, in simulation and with real robots.

Place, publisher, year, edition, pages
Delft, The Netherlands: AAAI Press, 2018
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-64721 (URN)000492986200059 ()2-s2.0-85054990876 (Scopus ID)
Conference
International Conference on Automated Planning and Scheduling (ICAPS 2018), Delft, The Netherland, June 24-29, 2018
Projects
Semantic RobotsILIAD
Funder
Knowledge Foundation, 20140033EU, Horizon 2020, 732737Vinnova
Available from: 2018-01-31 Created: 2018-01-31 Last updated: 2019-11-12Bibliographically approved
Menicatti, R., Recchiuto, C. T., Bruno, B., Zaccaria, R., Khaliq, A. A., Köckemann, U., . . . Sgorbissa, A. (2018). Collaborative Development Within a Social Robotic, Multi-Disciplinary Effort: the CARESSES Case Study. In: 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO): . Paper presented at 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Genova, Italy, 27-29 September, 2018 (pp. 117-124). IEEE
Open this publication in new window or tab >>Collaborative Development Within a Social Robotic, Multi-Disciplinary Effort: the CARESSES Case Study
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2018 (English)In: 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), IEEE, 2018, p. 117-124Conference paper, Published paper (Refereed)
Abstract [en]

In many cases, complex multidisciplinary research projects may show a lack of coordinated development and integration, and a big effort is often required in the final phase of the projects in order to merge software developed by heterogeneous research groups. This is particularly true in advanced robotic projects: the objective here is to deliver a system that integrates all the hardware and software components, is capable of autonomous behaviour, and needs to be deployed in real-world scenarios toward providing an impact on future research and, ultimately, on society. On the other hand, in recent years there has been a growing interest for techniques related to software integration, but these have been mostly applied to the IT commercial domain.

This paper presents the work performed in the context of the project CARESSES, a multidisciplinary research project focusing on socially assistive robotics that involves 9 partners from the EU and Japan. Given the complexity of the project, a huge importance has been placed on software integration, task planning and architecture definition since the first stages of the work: to this aim, some of the practices commonly used in the commercial domain for software integration, such as merging software from the early stage, have been applied. As a case study, the document describes the steps which have been followed in the first year of the project discussing strengths and weaknesses of this approach.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Workshop on Advanced Robotics and its Social Impacts, ISSN 2162-7568
Keywords
Robot sensing systems, Cultural differences, Robot kinematics, Computer architecture, Middleware
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-71984 (URN)10.1109/ARSO.2018.8625740 (DOI)000458688000025 ()978-1-5386-8037-7 (ISBN)
Conference
2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Genova, Italy, 27-29 September, 2018
Projects
CARESSES
Funder
EU, Horizon 2020, 737858
Note

Funding Agencies:

Ministry of Internal Affairs and Communication of Japan 

Available from: 2019-01-31 Created: 2019-01-31 Last updated: 2019-03-01Bibliographically approved
Khaliq, A. A., Köckemann, U., Pecora, F., Saffiotti, A., Bruno, B., Recchiuto, C. T., . . . Chong, N. Y. (2018). Culturally aware Planning and Execution of Robot Actions. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): . Paper presented at 25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018 (pp. 326-332). IEEE
Open this publication in new window or tab >>Culturally aware Planning and Execution of Robot Actions
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2018 (English)In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2018, p. 326-332Conference paper, Published paper (Refereed)
Abstract [en]

The way in which humans behave, speak andinteract is deeply influenced by their culture. For example,greeting is done differently in France, in Sweden or in Japan;and the average interpersonal distance changes from onecultural group to the other. In order to successfully coexistwith humans, robots should also adapt their behavior to theculture, customs and manners of the persons they interact with.In this paper, we deal with an important ingredient of culturaladaptation: how to generate robot plans that respect givencultural preferences, and how to execute them in a way thatis sensitive to those preferences. We present initial results inthis direction in the context of the CARESSES project, a jointEU-Japan effort to build culturally competent assistive robots.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858, E-ISSN 2153-0866
Keywords
Robotics, automated planning, cultural awareness
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-71980 (URN)10.1109/IROS.2018.8593570 (DOI)000458872700030 ()978-1-5386-8094-0 (ISBN)978-1-5386-8095-7 (ISBN)
Conference
25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018
Funder
EU, Horizon 2020, 737858
Note

Funding Agency:

Ministry of Internal Affairs and Communication of Japan

Available from: 2019-01-31 Created: 2019-01-31 Last updated: 2019-03-14Bibliographically approved
Köckemann, U., Khaliq, A. A., Pecora, F. & Saffiotti, A. (2018). Domain Reasoning for Robot Task Planning: A Position Paper. In: Alberto Finzi, Erez Karpas, Goldie Nejat, AndreA Orlandini, Siddharth Srivastava (Ed.), PlanRob 2018: Proceedings of the 6th Workshop on Planning and Robotics. Paper presented at 28th International Conference on Automated Planning and Scheduling, Delft, The Netherlands, June 24-29, 2018 (pp. 102-105). ICAPS
Open this publication in new window or tab >>Domain Reasoning for Robot Task Planning: A Position Paper
2018 (English)In: PlanRob 2018: Proceedings of the 6th Workshop on Planning and Robotics / [ed] Alberto Finzi, Erez Karpas, Goldie Nejat, AndreA Orlandini, Siddharth Srivastava, ICAPS , 2018, p. 102-105Conference paper, Published paper (Refereed)
Abstract [en]

In this position paper we argue for moving towards generalpurpose domains to promote the usage of task planning forreal-world robot systems. Planning approaches should extractconcrete domains based on their current context in order tosolve problems. Towards this aim, we define the problem ofdomain reasoning, by which a planning domain is obtainedfrom a more general, multi-purpose domain definition, giventhe current deployment and context of the robot system. Weprovide examples motivating the need for domain reasoningin robot task planning, as well as a discussion of potentialsolutions to the domain reasoning problem.

Place, publisher, year, edition, pages
ICAPS, 2018
Keywords
Automated planning, domain reasoning
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-71979 (URN)
Conference
28th International Conference on Automated Planning and Scheduling, Delft, The Netherlands, June 24-29, 2018
Projects
CARESSES
Funder
EU, Horizon 2020, 737858
Available from: 2019-01-31 Created: 2019-01-31 Last updated: 2019-02-04Bibliographically approved
Salvado, J., Krug, R., Mansouri, M. & Pecora, F. (2018). Motion Planning and Goal Assignment for Robot Fleets Using Trajectory Optimization. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): . Paper presented at 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018 (pp. 7940-7946). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Motion Planning and Goal Assignment for Robot Fleets Using Trajectory Optimization
2018 (English)In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 7940-7946Conference paper, Published paper (Refereed)
Abstract [en]

This paper is concerned with automating fleets of autonomous robots. This involves solving a multitude of problems, including goal assignment, motion planning, and coordination, while maximizing some performance criterion. While methods for solving these sub-problems have been studied, they address only a facet of the overall problem, and make strong assumptions on the use-case, on the environment, or on the robots in the fleet. In this paper, we formulate the overall fleet management problem in terms of Optimal Control. We describe a scheme for solving this problem in the particular case of fleets of non-holonomic robots navigating in an environment with obstacles. The method is based on a two-phase approach, whereby the first phase solves for fleet-wide boolean decision variables via Mixed Integer Quadratic Programming, and the second phase solves for real-valued variables to obtain an optimized set of trajectories for the fleet. Examples showcasing the features of the method are illustrated, and the method is validated experimentally.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858, E-ISSN 2153-0866
Keywords
Multi robot motion planning
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:oru:diva-71289 (URN)10.1109/IROS.2018.8594118 (DOI)000458872707027 ()978-1-5386-8094-0 (ISBN)978-1-5386-8095-7 (ISBN)
Conference
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 1-5, 2018
Projects
ILIAD
Funder
EU, Horizon 2020, 732737VINNOVASwedish Foundation for Strategic Research
Available from: 2019-01-09 Created: 2019-01-09 Last updated: 2019-03-13Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-9652-7864

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