Interacting with team oriented plans in multi-robot systems

Team oriented plans have become a popular tool for operators to control teams of autonomous robots to pursue complex objectives in complex environments. Such plans allow an operator to specify high level directives and allow the team to autonomously determine how to implement such directives. However, the operators will often want to interrupt the activities of individual team members to deal with particular situations, such as a danger to a robot that the robot team cannot perceive. Previously, after such interrupts, the operator would usually need to restart the team plan to ensure its success. In this paper, we present an approach to encoding how interrupts can be smoothly handled within a team plan. Building on a team plan formalism that uses Colored Petri Nets, we describe a mechanism that allows a range of interrupts to be handled smoothly, allowing the team to efficiently continue with its task after the operator intervention. We validate the approach with an application of robotic watercraft and show improved overall efficiency. In particular, we consider a situation where several platforms should travel through a set of pre-specified locations, and we identify three specific cases that require the operator to interrupt the plan execution: (i) a boat must be pulled out; (ii) all boats should stop the plan and move to a pre-specified assembly position; (iii) a set of boats must synchronize to traverse a dangerous area one after the other. Our experiments show that the use of our interrupt mechanism decreases the time to complete the plan (up to 48 % reduction) and decreases the operator load (up to 80 % reduction in number of user actions). Moreover, we performed experiments with real robotic platforms to validate the applicability of our mechanism in the actual deployment of robotic watercraft.

[1]  Alessandro Farinelli,et al.  A Mechanism for Smoothly Handling Human Interrupts in Team Oriented Plans , 2015, AAMAS.

[2]  Peter Radford,et al.  Petri Net Theory and the Modeling of Systems , 1982 .

[3]  Animesh Dutta,et al.  Task Petri Nets for Agent Based Computing , 2015 .

[4]  Gaurav S. Sukhatme,et al.  Adaptive teams of autonomous aerial and ground robots for situational awareness , 2007, J. Field Robotics.

[5]  Michael Westergaard,et al.  CPN Tools for Editing, Simulating, and Analysing Coloured Petri Nets , 2003, ICATPN.

[6]  K. Suzanne Barber,et al.  Dynamic adaptive autonomy in multi-agent systems , 2000, J. Exp. Theor. Artif. Intell..

[7]  Michail G. Lagoudakis,et al.  The Generation of Bidding Rules for Auction-Based Robot Coordination , 2005 .

[8]  Maria L. Gini,et al.  Mixed-initiative decision support in agent-based automated contracting , 2000, AGENTS '00.

[9]  Ray G. Gosine,et al.  Coordinated execution of tasks in a multiagent environment , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[10]  Cohen Phil Teamwork: Special Issue on Cognitive Science and Artificial Intelligence , 1991 .

[11]  Pedro U. Lima,et al.  Petri Net Plans , 2011, Autonomous Agents and Multi-Agent Systems.

[12]  Limor Marciano,et al.  of Single-Robot and Multi-Robot Plans , 2013 .

[13]  Didier Lime,et al.  Reachability Problems and Abstract State Spaces for Time Petri Nets with Stopwatches , 2007, Discret. Event Dyn. Syst..

[14]  Gal A. Kaminka,et al.  Flexible Teamwork in Behavior-Based Robots , 2005, AAAI.

[15]  Michael Lewis,et al.  Human control for cooperating robot teams , 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  Katia P. Sycara,et al.  The RETSINA MAS, a Case Study , 2002, SELMAS.

[17]  Robin R. Murphy,et al.  Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[18]  John Yen,et al.  Modeling and verifying multi-agent behaviors using predicate/transition nets , 2002, SEKE '02.

[19]  Archie C. Chapman,et al.  Flood disaster mitigation: a real-world challenge problem for multi-agent unmanned surface vehicles , 2011, AAMAS'11.

[20]  Reid G. Simmons,et al.  A task description language for robot control , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[21]  Kamel Barkaoui,et al.  A New Formalism for Modeling a Multi Agent Systems: Agent Petri Nets , 2010, J. Softw. Eng. Appl..

[22]  Prasanna Velagapudi,et al.  Development of a Low Cost Multi-Robot Autonomous Marine Surface Platform , 2012, FSR.

[23]  Nicholas R. Jennings,et al.  Deploying the max-sum algorithm for decentralised coordination and task allocation of unmanned aerial vehicles for live aerial imagery collection , 2012, 2012 IEEE International Conference on Robotics and Automation.

[24]  Illah R. Nourbakhsh,et al.  Human-robot teaming for search and rescue , 2005, IEEE Pervasive Computing.

[25]  Milind Tambe,et al.  Towards Flexible Teamwork , 1997, J. Artif. Intell. Res..

[26]  Lars Michael Kristensen,et al.  Coloured Petri Nets - Modelling and Validation of Concurrent Systems , 2009 .

[27]  Pedro U. Lima,et al.  Robot task plan representation by Petri nets: modelling, identification, analysis and execution , 2012, Auton. Robots.

[28]  Fei-Yue Wang,et al.  A Petri-net coordination model for an intelligent mobile robot , 1991, IEEE Trans. Syst. Man Cybern..

[29]  M. Ani Hsieh,et al.  Adaptive teams of autonomous aerial and ground robots for situational awareness: Field Reports , 2007 .

[30]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[31]  Milind Tambe,et al.  Towards Adjustable Autonomy for the Real World , 2002, J. Artif. Intell. Res..

[32]  Wolfgang Reisig,et al.  Lectures on Concurrency and Petri Nets , 2003, Lecture Notes in Computer Science.