Bottom-up motion and task coordination for loosely-coupled multi-agent systems with dependent local tasks

We propose a bottom-up motion and task coordination scheme for loosely-coupled multi-agent systems under dependent local tasks. Instead of defining a global task for the whole team, each agent is assigned locally a task as syntactically co-safe linear temporal logic formulas that specify both motion and action requirements. Inter-agent dependency is introduced by collaborative actions of which the execution requires multiple agents' collaboration. The proposed solution contains an offline initial plan synthesis, an on-line request-reply messages exchange and a real-time plan adaptation algorithm. It is distributed in that any decision is made locally based on local computation and local communication within neighboring agents. It is scalable and resilient to agent failures as the dependency is formed and removed dynamically based on the plan execution status and agent capabilities, instead of pre-assigned agent identities. The overall scheme is demonstrated by a simulated scenario.

[1]  Antonio Bicchi,et al.  Symbolic planning and control of robot motion [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.

[2]  Emilio Frazzoli,et al.  Vehicle Routing with Linear Temporal Logic Specifications: Applications to Multi-UAV Mission Planning , 2008 .

[3]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[4]  Ufuk Topcu,et al.  Receding horizon control for temporal logic specifications , 2010, HSCC '10.

[5]  Dimos V. Dimarogonas,et al.  Reconfiguration in motion planning of single- and multi-agent systems under infeasible local LTL specifications , 2013, 52nd IEEE Conference on Decision and Control.

[6]  Dimos V. Dimarogonas,et al.  Multi-agent plan reconfiguration under local LTL specifications , 2015, Int. J. Robotics Res..

[7]  Dimos V. Dimarogonas,et al.  A receding horizon approach to multi-agent planning from local LTL specifications , 2014, 2014 American Control Conference.

[8]  Lydia E. Kavraki,et al.  Sampling-based motion planning with temporal goals , 2010, 2010 IEEE International Conference on Robotics and Automation.

[9]  Karl Henrik Johansson,et al.  Motion and action planning under LTL specifications using navigation functions and action description language , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Christel Baier,et al.  Principles of model checking , 2008 .

[11]  K.J. Kyriakopoulos,et al.  Automatic synthesis of multi-agent motion tasks based on LTL specifications , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[12]  Calin Belta,et al.  Optimality and Robustness in Multi-Robot Path Planning with Temporal Logic Constraints , 2013, Int. J. Robotics Res..

[13]  Georgios E. Fainekos,et al.  Revising temporal logic specifications for motion planning , 2011, 2011 IEEE International Conference on Robotics and Automation.

[14]  D. Dimarogonas,et al.  Decentralized multi-agent control from local LTL specifications , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[15]  Yushan Chen,et al.  Automatic Deployment of Robotic Teams , 2011, IEEE Robotics & Automation Magazine.

[16]  U. Topcu,et al.  Correct , Reactive Robot Control from Abstraction and Temporal Logic Specifications , 2011 .

[17]  Ufuk Topcu,et al.  Correct, Reactive, High-Level Robot Control , 2011, IEEE Robotics & Automation Magazine.

[18]  Orna Kupferman,et al.  Model Checking of Safety Properties , 1999, Formal Methods Syst. Des..

[19]  G. Nemhauser,et al.  Integer Programming , 2020 .

[20]  Paul Gastin,et al.  Fast LTL to Büchi Automata Translation , 2001, CAV.

[21]  Calin Belta,et al.  Multi-robot deployment from LTL specifications with reduced communication , 2011, IEEE Conference on Decision and Control and European Control Conference.

[22]  George J. Pappas,et al.  Symbolic Planning and Control of Robot Motion Finding the Missing Pieces of Current Methods and Ideas , .