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  • 1. Ciccozzi, F.
    et al.
    Di Ruscio, D.
    Malavolta, I.
    Pelliccione, P.
    Tumova, Jana
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
    Engineering the software of robotic systems2017In: Proceedings - 2017 IEEE/ACM 39th International Conference on Software Engineering Companion, ICSE-C 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 507-508, article id 7965406Conference paper (Refereed)
    Abstract [en]

    The production of software for robotic systems is often case-specific, without fully following established engineering approaches. Systematic approaches, methods, models, and tools are pivotal for the creation of robotic systems for real-world applications and turn-key solutions. Well-defined (software) engineering approaches are considered the 'make or break' factor in the development of complex robotic systems. The shift towards well-defined engineering approaches will stimulate component supply-chains and significantly reshape the robotics marketplace. The goal of this technical briefing is to provide an overview on the state of the art and practice concerning solutions and open challenges in the engineering of software required to develop and manage robotic systems. Model-Driven Engineering (MDE) is discussed as a promising technology to raise the level of abstraction, promote reuse, facilitate integration, boost automation and promote early analysis in such a complex domain.

  • 2.
    Guo, Meng
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Boskos, Dimitris
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Distributed hybrid control synthesis for multi-agent systems from high-level specifications2018In: Control Subject to Computational and Communication Constraints, Springer Verlag , 2018, 475, p. 241-260Chapter in book (Refereed)
    Abstract [en]

    Current control applications necessitate in many cases the consideration of systems with multiple interconnected components. These components/agents may need to fulfill high-level tasks at a discrete planning layer and also coupled constraints at the continuous control layer. Toward this end, the need for combined decentralized control at the continuous layer and planning at the discrete layer becomes apparent. While there are approaches that handle the problem in a top-down centralized manner, decentralized bottom-up approaches have not been pursued to the same extent. We present here some of our results for the problem of combined, hybrid control and task planning from high-level specifications for multi-agent systems in a bottom-up manner. In the first part, we present some initial results on extending the necessary notion of abstractions to multi-agent systems in a distributed fashion. We then consider a setup where agents are assigned individual tasks in the form of linear temporal logic (LTL) formulas and derive local task planning strategies for each agent. In the last part, the problem of combined distributed task planning and control under coupled continuous constraints is further considered.

  • 3.
    Guo, Meng
    et al.
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Tumova, Jana
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Communication-Free Multi-Agent Control Under Local Temporal Tasks and Relative-Distance Constraints2016In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 61, no 12, p. 3948-3962Article in journal (Refereed)
    Abstract [en]

    We propose a distributed control and coordination strategy for multi-agent systems where each agent has a local task specified as a Linear Temporal Logic (LTL) formula and at the same time is subject to relative-distance constraints with its neighboring agents. The local tasks capture the temporal requirements on individual agents' behaviors, while the relative-distance constraints impose requirements on the collective motion of the whole team. The proposed solution relies only on relative-state measurements among the neighboring agents without the need for explicit information exchange. It is guaranteed that the local tasks given as syntactically co-safe or general LTL formulas are fulfilled and the relative-distance constraints are satisfied at all time. The approach is demonstrated with computer simulations.

  • 4.
    Guo, Meng
    et al.
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Tumova, Jana
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Automatic Control.
    Dimarogonas, Dimos V
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Cooperative decentralized multi-agent control under local LTL tasks and connectivity constraints2014In: Proceedings of the IEEE Conference on Decision and Control, IEEE conference proceedings, 2014, no February, p. 75-80Conference paper (Refereed)
    Abstract [en]

    We propose a framework for the decentralized control of a team of agents that are assigned local tasks expressed as Linear Temporal Logic (LTL) formulas. Each local LTL task specification captures both the requirements on the respective agent's behavior and the requests for the other agents' collaborations needed to accomplish the task. Furthermore, the agents are subject to communication constraints. The presented solution follows the automata-theoretic approach to LTL model checking, however, it avoids the computationally demanding construction of synchronized product system between the agents. A decentralized coordination scheme through a dynamic leader selection is proposed, to guarantee the low-level connectivity maintenance and a progress towards the satisfaction of each agent's task.

  • 5.
    Guo, Meng
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Tumova, Jana
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Dimarogonas, Dino V.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hybrid control of multi-agent systems under local temporal tasks and relative-distance constraints2016In: Proceedings of the IEEE Conference on Decision and Control, IEEE conference proceedings, 2016, p. 1701-1706Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a distributed hybrid control strategy for multi-agent systems where each agent has a local task specified as a Linear Temporal Logic (LTL) formula and at the same time is subject to relative-distance constraints with its neighboring agents. The local tasks capture the temporal requirements on individual agents' behaviors, while the relative-distance constraints impose requirements on the collective motion of the whole team. The proposed solution relies only on relative-state measurements among the neighboring agents without the need for explicit information exchange. It is guaranteed that the local tasks given as syntactically co-safe or general LTL formulas are fulfilled and the relative-distance constraints are satisfied at all time. The approach is demonstrated with computer simulations.

  • 6.
    Karlsson, Jesper
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH Royal Inst Technol, Stockholm, Sweden..
    Vasile, Cristian-Ioan
    MIT, Cambridge, MA 02139 USA..
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH Royal Inst Technol, Stockholm, Sweden..
    Karaman, Sertac
    MIT, Cambridge, MA 02139 USA..
    Rus, Daniela
    MIT, Cambridge, MA 02139 USA..
    Multi-vehicle motion planning for social optimal mobility-on-demand2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE COMPUTER SOC , 2018, p. 7298-7305Conference paper (Refereed)
    Abstract [en]

    In this paper we consider a fleet of self-driving cars operating in a road network governed by rules of the road, such as the Vienna Convention on Road Traffic, providing rides to customers to serve their demands with desired deadlines. We focus on the associated motion planning problem that tradesoff the demands' delays and level of violation of the rules of the road to achieve social optimum among the vehicles. Due to operating in the same environment, the interaction between the cars must be taken into account, and can induce further delays. We propose an integrated route and motion planning approach that achieves scalability with respect to the number of cars by resolving potential collision situations locally within so-called bubble spaces enclosing the conflict. The algorithms leverage the road geometries, and perform joint planning only for lead vehicles in the conflict and use queue scheduling for the remaining cars. Furthermore, a framework for storing previously resolved conflict situations is proposed, which can be use for quick querying of joint motion plans. We show the mobility-on-demand setup and effectiveness of the proposed approach in simulated case studies involving up to 10 selfdriving vehicles.

  • 7. Menghi, C.
    et al.
    Garcia, S.
    Pelliccione, P.
    Tumova, Jana
    KTH.
    Multi-robot LTL planning under uncertainty2018In: 22nd International Symposium on Formal Methods, FM 2018 Held as Part of the Federated Logic Conference, FloC 2018, Springer, 2018, Vol. 10951, p. 399-417Conference paper (Refereed)
    Abstract [en]

    Robot applications are increasingly based on teams of robots that collaborate to perform a desired mission. Such applications ask for decentralized techniques that allow for tractable automated planning. Another aspect that current robot applications must consider is partial knowledge about the environment in which the robots are operating and the uncertainty associated with the outcome of the robots’ actions. Current planning techniques used for teams of robots that perform complex missions do not systematically address these challenges: (1) they are either based on centralized solutions and hence not scalable, (2) they consider rather simple missions, such as A-to-B travel, (3) they do not work in partially known environments. We present a planning solution that decomposes the team of robots into subclasses, considers missions given in temporal logic, and at the same time works when only partial knowledge of the environment is available. We prove the correctness of the solution and evaluate its effectiveness on a set of realistic examples.

  • 8. Menghi, C.
    et al.
    García, S.
    Pelliccione, P.
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Poster: Towards multi-robot applications planning under uncertainty2018In: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, IEEE Computer Society, 2018, p. 438-439Conference paper (Refereed)
    Abstract [en]

    Novel robotic applications are no longer based on single robots. They rather require teams of robots that collaborate and interact to perform a desired mission. They must also be used in contexts in which only partial knowledge about the robots and their environment is present. To ensure mission achievement, robotic applications require the usage of planners that compute the set of actions the robots must perform. Current planning techniques are often based on centralized solutions and hence they do not scale when teams of robots are considered, they consider rather simple missions, and they do not work in partially known environments. To address these challenges, we present a planning solution that decomposes the team of robots into subclasses, considers complex high-level missions given in temporal logic, and at the same time works when only partial knowledge of the environment is available.

  • 9.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Boskos, Dimitris
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    On the timed temporal logic planning of coupled multi-agent systems2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 97, p. 339-345Article in journal (Refereed)
    Abstract [en]

    This paper presents a fully automated procedure for controller synthesis for multi-agent systems under coupling constraints. Each agent is modeled with dynamics consisting of two terms: the first one models the coupling constraints and the other one is an additional bounded control input. We aim to design these inputs so that each agent meets an individual high-level specification given as a Metric Interval Temporal Logic (MITL). First, a decentralized abstraction that provides a space and time discretization of the multi-agent system is designed. Second, by utilizing this abstraction and techniques from formal verification, we propose an algorithm that computes the individual runs which provably satisfy the high-level tasks. The overall approach is demonstrated in a simulation example conducted in MATLAB environment. 

  • 10.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Boskos, Dimitris
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Tumova, Jana
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Cooperative planning for coupled multi-agent systems under timed temporal specifications2017In: 2017 American Control Conference (ACC) 24-26 May 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1847-1852, article id 7963221Conference paper (Refereed)
    Abstract [en]

    This paper presents a fully automated procedure for controller synthesis for multi-agent systems under coupling constraints. Each agent has dynamics consisting of two terms: The first one models the coupling constraints and the other one is an additional bounded control input. We aim to design these inputs so that each agent meets an individual high-level specification given as a Metric Interval Temporal Logic (MITL). First, a decentralized abstraction that provides a time and space discretization of the multi-agent system is designed. Second, by utilizing this abstraction and techniques from formal verification, we provide an algorithm that computes the individual runs which provably satisfy the high-level tasks. The overall approach is demonstrated in a simulation example.

  • 11.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH Royal Inst Technol, Sch Elect Engn, ACCESS Linnaeus Ctr, SE-10044 Stockholm, Sweden.;KTH Ctr Autonomous Syst, Stockholm, Sweden..
    Boskos, Dimitris
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH Royal Inst Technol, Sch Elect Engn, ACCESS Linnaeus Ctr, SE-10044 Stockholm, Sweden.;KTH Ctr Autonomous Syst, Stockholm, Sweden..
    Tumova, Jana
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH Royal Inst Technol, Sch Elect Engn, ACCESS Linnaeus Ctr, SE-10044 Stockholm, Sweden.;KTH Ctr Autonomous Syst, Stockholm, Sweden..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH Royal Inst Technol, Sch Elect Engn, ACCESS Linnaeus Ctr, SE-10044 Stockholm, Sweden.;KTH Ctr Autonomous Syst, Stockholm, Sweden..
    Cooperative Planning for Coupled Multi-Agent Systems under Timed Temporal Specifications2017In: 2017 AMERICAN CONTROL CONFERENCE (ACC), IEEE , 2017, p. 1847-1852Conference paper (Refereed)
    Abstract [en]

    This paper presents a fully automated procedure for controller synthesis for multi-agent systems under coupling constraints. Each agent has dynamics consisting of two terms: the first one models the coupling constraints and the other one is an additional bounded control input. We aim to design these inputs so that each agent meets an individual high-level specification given as a Metric Interval Temporal Logic (MITL). First, a decentralized abstraction that provides a time and space discretization of the multi-agent system is designed. Second, by utilizing this abstraction and techniques from formal verification, we provide an algorithm that computes the individual runs which provably satisfy the high-level tasks. The overall approach is demonstrated in a simulation example.

  • 12.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Tumova, Jana
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Cooperative Task Planning of Multi-Agent Systems Under TimedTemporal Specifications2016In: Proceedings of the American Control Conference, 2016, p. 7104-7109Conference paper (Refereed)
    Abstract [en]

    In this paper the problem of cooperative taskplanning of multi-agent systems when timed constraints areimposed to the system is investigated. We consider timedconstraints given by Metric Interval Temporal Logic (MITL).We propose a method for automatic control synthesis in a two-stage systematic procedure. With this method we guarantee thatall the agents satisfy their own individual task specifications aswell as that the team satisfies a team global task specification.

  • 13.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Tumova, Jana
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Probabilistic Plan Synthesis for Coupled Multi-Agent Systems2017Conference paper (Refereed)
  • 14.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Tumova, Jana
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Probabilistic Plan Synthesis for Coupled Multi-Agent Systems2017In: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 50, no 1, p. 10766-10771Article in journal (Refereed)
    Abstract [en]

    This paper presents a fully automated procedure for controller synthesis for multi-agent systems under the presence of uncertainties. We model the motion of each of the N agents in the environment as a Markov Decision Process (MDP) and we assign to each agent one individual high-level formula given in Probabilistic Computational Tree Logic (PCTL). Each agent may need to collaborate with other agents in order to achieve a task. The collaboration is imposed by sharing actions between the agents. We aim to design local control policies such that each agent satisfies its individual PCTL formula. The proposed algorithm builds on clustering the agents, MDP products construction and controller policies design. We show that our approach has better computational complexity than the centralized case, which traditionally suffers from very high computational demands.

  • 15.
    Reyes Castro, Luis
    et al.
    MIT.
    Chaudhari, Pratik
    MIT.
    Tumova, Jana
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Karaman, Sertac
    MIT.
    Frazzoli, Emilio
    MIT.
    Rus, Daniela
    MIT.
    Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning2013In: 2013 IEEE 52ND ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE conference proceedings, 2013, p. 3217-3224Conference paper (Refereed)
    Abstract [en]

    This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules are violated. The proposed algorithm computes a control law, that minimizes the level of unsafety while the desired goal is guaranteed to be reached. This problem is motivated by an autonomous car navigating an urban environment while following rules of the road such as "always travel in right lane" and "do not change lanes frequently". Ideas behind sampling based motion-planning algorithms, such as Probabilistic Road Maps (PRMs) and Rapidly-exploring Random Trees (RRTs), are employed to incrementally construct a finite concretization of the dynamics as a durational Kripke structure. In conjunction with this, a weighted finite automaton that captures the safety rules is used in order to find an optimal trajectory that minimizes the violation of safety rules. We prove that the proposed algorithm guarantees asymptotic optimality, i.e., almost-sure convergence to optimal solutions. We present results of simulation experiments and an implementation on an autonomous urban mobility-on-demand system.

  • 16. Tsiamis, Anastasios
    et al.
    Tumova, Jana
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Bechlioulis, Charalampos P.
    Karras, George C.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Kyriakopoulos, Kostas J.
    Decentralized Leader-Follower Control under High Level Goals without Explicit Communication2015In: 2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), IEEE , 2015, p. 5790-5795Conference paper (Refereed)
    Abstract [en]

    In this paper, we study the decentralized control problem of a two-agent system under local goal specifications given as temporal logic formulas. The agents collaboratively carry an object in a leader-follower scheme and lack means to exchange messages on-line, i. e., to communicate explicitly. Specifically, we propose a decentralized control protocol and a leader re-election strategy that secure the accomplishment of both agents' local goal specifications. The challenge herein lies in exploiting exclusively implicit inter- robot communication that is a natural outcome of the physical interaction of the robots with the object. An illustrative experiment is included clarifying and verifying the approach.

  • 17.
    Tumova, Jana
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Receding Horizon Approach to Multi-Agent Planning from Local LTL Specifications2014Conference paper (Refereed)
    Abstract [en]

    We study the problem of control synthesis for multi-agent systems, to achieve complex, high-level, long-term goals that are assigned to each agent individually. As the agents might not be capable of satisfying their respective goals by themselves, requests for other agents' collaborations are a part of the task descriptions. Particularly, we consider that the task specification takes a form of a linear temporal logic formula, which may contain requirements and constraints on the other agent's behavior. A traditional automata-based approach to multi-agent strategy synthesis from such specifications builds on centralized planning for the whole team and thus suffers from extreme computational demands. In this work, we aim at reducing the computational complexity by decomposing the strategy synthesis problem into short horizon planning problems that are solved iteratively, upon the run of the agents. We discuss the correctness of the solution and find assumptions, under which the proposed iterative algorithm leads to provable eventual satisfaction of the desired specifications.

  • 18.
    Tumova, Jana
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Multi-agent planning under local LTL specifications and event-based synchronization2016In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 70, p. 239-248Article in journal (Refereed)
    Abstract [en]

    We study the problem of plan synthesis for multi-agent systems, to achieve complex, high-level, long-term goals that are assigned to each agent individually. As the agents might not be capable of satisfying their respective goals by themselves, requests for other agents' collaborations are a part of the task descriptions. We consider that each agent is modeled as a discrete state-transition system and its task specification takes a form of a linear temporal logic formula. A traditional automata-based approach to multi-agent plan synthesis from such specifications builds on centralized team planning and full team synchronization after each agents' discrete step, and thus suffers from extreme computational demands. We aim at reducing the computational complexity by decomposing the plan synthesis problem into finite horizon planning problems that are solved iteratively, upon the run of the agents. We introduce an event-based synchronization that allows our approach to efficiently adapt to different time durations of different agents' discrete steps. We discuss the correctness of the solution and find assumptions, under which the proposed iterative algorithm leads to provable eventual satisfaction of the desired specifications.

  • 19.
    Tumova, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Synthesizing least-limiting guidelines for safety of semi-autonomous systems2016In: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 5714-5719, article id 7799147Conference paper (Refereed)
    Abstract [en]

    We consider the problem of synthesizing safe-by-design control strategies for semi-autonomous systems. Our aim is to address situations when safety cannot be guaranteed solely by the autonomous, controllable part of the system and a certain level of collaboration is needed from the uncontrollable part, such as the human operator. In this paper, we propose a systematic solution to generating least-limiting guidelines, i.e. the guidelines that restrict the human operator as little as possible in the worst-case long-term system executions. The algorithm leverages ideas from 2-player turn-based games.

  • 20.
    Tumova, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dino V.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Decomposition of multi-agent planning under distributed motion and task LTL specifications2016In: Proceedings of the IEEE Conference on Decision and Control, IEEE conference proceedings, 2016, p. 7448-7453Conference paper (Refereed)
    Abstract [en]

    The aim of this work is to introduce an efficient procedure for discrete multi-agent planning under local complex temporal logic behavior specifications. While the first part of an agent's behavior specification constraints the agent's trace and is independent, the second part of the specification expresses the agent's tasks in terms of the services to be provided along the trace and may impose requests for the other agents' collaborations. To fight the extreme computational complexity of centralized multi-agent planning, we propose a two-phase automata-based solution, where we systematically decouple the planning procedure for the two types of specifications. At first, we only consider the former specifications in a fully decentralized way and we compactly represent each agents' admissible traces by abstracting away the states that are insignificant for the satisfaction of their latter specifications. Second, the synchronized planning procedure uses only the compact representations. The satisfaction of the overall specification is guaranteed by construction for each agent.

  • 21.
    Tumova, Jana
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Karaman, S.
    Belta, C.
    Rus, D.
    Least-Violating Planning in Road Networks from Temporal Logic Specifications2016In: 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems, ICCPS 2016 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2016, article id 7479106Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider the problem of automated plan synthesis for a vehicle operating in a road network, which is modeled as a weighted transition system. The vehicle is assigned a set of demands, each of which involves a task specification in the form of a syntactically co-safe LTL formula, a deadline for achieving this task, and a demand priority. The demands arrive gradually, upon the run of the vehicle, and hence periodical replanning is needed. We particularly focus on cases, where all tasks cannot be accomplished within the desired deadlines and propose several different ways to measure the degree of demand violation that take into account the demand priorities. We develop a general solution to the problem of least-violating planning and replanning based on a translation to linear programming problem. Furthermore, for a particular subclass of demands, we provide a more efficient solution based on graph search algorithms. The benefits of the approach are demonstrated through illustrative simulations inspired by mobility-on-demand scenarios.

  • 22.
    Tumova, Jana
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Marzinotto, Alejandro
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Kragic, Danica
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Maximally Satisfying LTL Action Planning2014In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS 2014), IEEE , 2014, p. 1503-1510Conference paper (Refereed)
    Abstract [en]

    We focus on autonomous robot action planning problem from Linear Temporal Logic (LTL) specifications, where the action refers to a "simple" motion or manipulation task, such as "go from A to B" or "grasp a ball". At the high-level planning layer, we propose an algorithm to synthesize a maximally satisfying discrete control strategy while taking into account that the robot's action executions may fail. Furthermore, we interface the high-level plan with the robot's low-level controller through a reactive middle-layer formalism called Behavior Trees (BTs). We demonstrate the proposed framework using a NAO robot capable of walking, ball grasping and ball dropping actions.

  • 23. Vasile, C. -I
    et al.
    Tumova, Jana
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
    Karaman, S.
    Belta, C.
    Rus, D.
    Minimum-violation scLTL motion planning for mobility-on-demand2017In: 2017 IEEE International Conference on Robotics and Automation (ICRA), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1481-1488, article id 7989177Conference paper (Refereed)
    Abstract [en]

    This work focuses on integrated routing and motion planning for an autonomous vehicle in a road network. We consider a problem in which customer demands need to be met within desired deadlines, and the rules of the road need to be satisfied. The vehicle might not, however, be able to satisfy these two goals at the same time. We propose a systematic way to compromise between delaying the satisfaction of the given demand and violating the road rules. We utilize scLTL formulas to specify desired behavior and develop a receding horizon approach including a periodically interacting routing algorithm and a RRT<-based motion planner. The proposed solution yields a provably minimum-violation trajectory. An illustrative case study is included.

1 - 23 of 23
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