Path planning of multirobot systems using Petri net models. Results and open problems

[EN] This paper presents a trajectory planning approach in multirobot systems based on Petri net models. This type of models is very useful for high-level specifications since, in this case, the classical planning methods (potential functions, RRT algorithms, RRT*) cannot be used being dicult to determine a priori the sequence of configurations for each robot. This work presents the formal definition of the Robot Motion Petri net t hat i s obtained from a partition of the environment in cells. Using the s tructure of the Petri net, in case of specifications defined as Boolean or Linear Temporal Logic (LTL) formulas, dierent optimization problems are presented that can be used to obtain trajectories for robots. The main advantage of models based on Petri nets is their scalability with respect to the number of robots. This makes it possible to reciently solve planning problems with a large number of robots. In the second part of the paper, some extensions and new results for distributed planning in unknown environments and with partial communications between robots are presented.[ES] Este trabajo presenta una estrategia de planificacón de trayectorias en equipos de robots moviles basada en el uso de modelos definidos con redes de Petri. Estos tipos de modelos son muy útiles para especificaciones de alto nivel ya que, en este caso, los métodos clásicos de planificación (funciones potenciales, algoritmos RRT, RRT*) no se pueden utilizar, siendo difícil determinar a priori la secuencia de configuraciones para cada robot. Este trabajo presenta la definición formal de la Red de Petri de Movimiento de Robots que se obtiene a partir de una partición del entorno en celdas. Utilizando la estructura de la red de Petri, en caso de especificaciones definidas como fórmulas Booleanas o fórmulas en lógica temporal lineal (LTL), se presentan diferentes problemas de optimización que se pueden utilizar para obtener trayectorias para los robots. La principal ventaja de los modelos basados en redes de Petri es su escalabilidad con respecto al número de robots. Ello permite resolver con eficiencia problemas de planificación de equipos con un número grande de robots. En la segunda parte del trabajo, se presentan algunas extensiones y resultados nuevos para la planificación distribuida en entornos desconocidos y con comunicaciones parciales entre los robots.Los resultados de esta línea de investigación son fruto de la participación de varios compañeros, investigadores de la Universidad de Zaragoza y de otras Universidades extranjeras. Queremos agradecer la participación de todos ellos, mencionando muy especialmente a Marius Kloetzer (profesor de la Universidad Técnica de Iasi, Rumanía). Este trabajo ha sido financiado parcialmente por los proyectos PGC2018-098719-B-I00 and PGC2018-098817-A-I00 (MCIU/AEI/FEDER, UE) y la ONR Global NICOP grant N62909-19-1-2027.Mahulea, C.; González, R.; Montijano, E.; Silva, M. (2020). Planificación de trayectorias en sistemas multirobot utilizando redes de Petri. Resultados y problemas abiertos. Revista Iberoamericana de Automática e Informática industrial. 18(1):19-31. https://doi.org/10.4995/riai.2020.13785OJS1931181Baier, C., Katoen, J.P., 2008. Principles of model checking. MIT Press.Belta, C., Bicchi, A., Egerstedt, M., Frazzoli, E., Klavins, E., Pappas, G.-J., 2007. Symbolic planning and control of robot motion. IEEE Robotics and Automation Magazine 14 (1), 61-71. https://doi.org/10.1109/MRA.2007.339624Belta, C., Habets, L., 2006. 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Path planning for robotic teams based on LTL specifications and Petri net models. Discrete Event Dynamic Systems: Theory and Applications 30 (1), 55-79. https://doi.org/10.1007/s10626-019-00300-1Lacerda, B., Lima, P. U., 2019. Petri net based multi-robot task coordination from temporal logic specifications. Robotics and Autonomous Systems 122, 343-352. https://doi.org/10.1016/j.robot.2019.103289LaValle, S. M., 2006. Planning Algorithms. Cambridge, available at http://planning.cs.uiuc.edu. https://doi.org/10.1017/CBO9780511546877Leahy, K., Cristofalo, E., Vasile, C.-I., Jones, A., Montijano, E., Schwager, M., Belta, C., 2019. Control in belief space with temporal logic specifications using vision-based localization. The International Journal of Robotics Research 38 (6), 702-722. https://doi.org/10.1177/0278364919846340Mahulea, C., Kloetzer, M., 2018. Robot Planning based on Boolean Specifications using Petri Net Models. IEEE Trans. on Automatic Control 63 (7), 2218-2225. https://doi.org/10.1109/TAC.2017.2760249Mahulea, C., Kloetzer, M., Gonzalez, R., 2020a. Path Planning of Cooperative ' Mobile Robots Using Discrete Event Models. IEEE Wiley. https://doi.org/10.1002/9781119486305Mahulea, C., Kloetzer, M., Lesage, J.-J., 2020b. Multi-robot path planning with boolean specifications and collision avoidance. In: WODES'2020: 15th Workshop on Discrete Event Systems.Mahulea, C., Montijano, E., Kloetzer, M., 2020c. Distributed Multirobot Path Planning in Unknown Maps Using Petri Net Models. IFACPapersOnLine21th IFAC World Congress.Mesbahi, M., Egerstedt, M., 2010. Graph theoretic methods in multiagent networks. Princeton University Press. https://doi.org/10.1515/9781400835355Montijano, E., Montijano, J.-I., Sagues, C., Feb 2013. Chebyshev polynomials in distributed consensus applications. 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A distributed knowledge-based approach to flexible automation : the contract-net framework

Includes bibliographical references (p. 26-29)

Zero-gravity movement studies

The use of computer graphics to simulate the movement of articulated animals and mechanisms has a number of uses ranging over many fields. Human motion simulation systems can be useful in education, medicine, anatomy, physiology, and dance. In biomechanics, computer displays help to understand and analyze performance. Simulations can be used to help understand the effect of external or internal forces. Similarly, zero-gravity simulation systems should provide a means of designing and exploring the capabilities of hypothetical zero-gravity situations before actually carrying out such actions. The advantage of using a simulation of the motion is that one can experiment with variations of a maneuver before attempting to teach it to an individual. The zero-gravity motion simulation problem can be divided into two broad areas: human movement and behavior in zero-gravity, and simulation of articulated mechanisms

On Multi-Robot Path Planning Based on Petri Net Models and LTL specifications

This work considers the path planning problem for a team of identical robots evolving in a known environment. The robots should satisfy a global specification given as a Linear Temporal Logic (LTL) formula over a set of regions of interest. The proposed method exploits the advantages of Petri net models for the team of robots and B\"uchi automata modeling the specification. The approach in this paper consists in combining the two models into one, denoted Composed Petri net and use it to find a sequence of action movements for the mobile robots, providing collision free trajectories to fulfill the specification. The solution results from a set of Mixed Integer Linear Programming (MILP) problems. The main advantage of the proposed solution is the completeness of the algorithm, meaning that a solution is found when exists, this representing the key difference with our previous work in [1]. The simulations illustrate comparison results between current and previous approaches, focusing on the computational complexity.Comment: submitted to IEEE Transactions on Automatic Control, 202

A cooperative multi-agent robotics system: design and modelling

This paper presents the development of the robotic multi-agent system SMART. In this system, the agent concept is applied to both hardware and software entities. Hardware agents are robots, with three and four legs, and an IP-camera that takes images of the scene where the cooperative task is carried out. Hardware agents strongly cooperate with software agents. These latter agents can be classified into image processing, communications, task management and decision making, planning and trajectory generation agents. To model, control and evaluate the performance of cooperative tasks among agents, a kind of PetriNet, called Work-Flow Petri Net, is used. Experimental results shows the good performance of the system

Multi-robot Motion Planning based on Nets-within-Nets Modeling and Simulation

This paper focuses on designing motion plans for a heterogeneous team of robots that has to cooperate in fulfilling a global mission. The robots move in an environment containing some regions of interest, and the specification for the whole team can include avoidances, visits, or sequencing when entering these regions of interest. The specification is expressed in terms of a Petri net corresponding to an automaton, while each robot is also modeled by a state machine Petri net. With respect to existing solutions for related problems, the current work brings the following contributions. First, we propose a novel model, denoted {High-Level robot team Petri Net (HLPN) system, for incorporating the specification and the robot models into the Nets-within-Nets paradigm. A guard function, named Global Enabling Function (gef), is designed to synchronize the firing of transitions such that the robot motions do not violate the specification. Then, the solution is found by simulating the HPLN system in a specific software tool that accommodates Nets-within-Nets. An illustrative example based on a Linear Temporal Logic (LTL) mission is described throughout the paper, complementing the proposed rationale of the framework.Comment: submitted to 62nd IEEE Conference on Decision and Control, Dec. 13-15, 202

Robot planning based on boolean specifications using petri net models

In this paper, we propose an automated method for planning a team of mobile robots such that a Boolean-based mission is accomplished. The task consists of logical requirements over some regions of interest for the agents'' trajectories and for their final states. In other words, we allow combinatorial specifications defining desired final states whose attainment includes visits to, avoidance of, and ending in certain regions. The path planning approach should select such final states that optimize a certain global cost function. In particular, we consider minimum expected traveling distance of the team and reduce congestions. A Petri net (PN) with outputs models the movement capabilities of the team and the regions of interest. The imposed specification is translated to a set of linear restrictions for some binary variables, the robot movement capabilities are formulated as linear constraints on PN markings, and the evaluations of the binary variables are linked with PN markings via linear inequalities. This allows us to solve an integer linear programming problem whose solution yields robotic trajectories satisfying the task

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE

Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams