Task Allocation and Coordination for Limited Capability Mobile Robots

In multi-robot systems, predefined task allocation and coordination may not always work as desired. This is due to the inability to entirely model all aspects of the robot’s interactions with the environment before task execution. Robots with limited capabilities also present the challenge of how their limited resources should be utilised to achieve the objectives of the global task. This paper presents a task allocation and coordination strategy for mobile robots with limited capabilities. To determine task-robot combinations, task allocation utilises a VOTS that represent a robot’s suitability for a task. Task allocation yields a team of robots comprising task managers and task executers. After task allocation, task executer robots execute the global task, while task manager robots monitor the performance of the global task. If the global task’s performance is not optimal, the task executer robots’ resource utilisation is varied using a feedback coordination mechanism. The task allocation and coordination strategy is applied to a multi-robot map building task and preliminary results are presented.

[1]  B. Grosz.  Collaborative Systems , 1996 .

[2]  Fabrice R. Noreils,et al.  Toward a Robot Architecture Integrating Cooperation between Mobile Robots: Application to Indoor Environment , 1993, Int. J. Robotics Res..

[3]  Lynne E. Parker,et al.  Building Multirobot Coalitions Through Automated Task Solution Synthesis , 2006, Proceedings of the IEEE.

[4]  Gaurav S. Sukhatme,et al.  Multi-robot task-allocation through vacancy chains , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[5]  Dale A. Carnegie,et al.  Memory-time tradeoffs in a path planning approach utilising limited memory robots , 2007 .

[6]  Gerhard Lakemeyer,et al.  Exploring artificial intelligence in the new millennium , 2003 .

[7]  Reid G. Simmons,et al.  First Results in the Coordination of Heterogeneous Robots for Large-Scale Assembly , 2000, ISER.

[8]  Maja J. Mataric,et al.  Multi-robot task allocation: analyzing the complexity and optimality of key architectures , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[9]  Nicholas R. Jennings,et al.  Controlling Cooperative Problem Solving in Industrial Multi-Agent Systems Using Joint Intentions , 1995, Artif. Intell..

[10]  Rachid Alami,et al.  M+: a scheme for multi-robot cooperation through negotiated task allocation and achievement , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[11]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant multirobot cooperation , 1998, IEEE Trans. Robotics Autom..

[12]  Iwan Ulrich,et al.  VFH+: reliable obstacle avoidance for fast mobile robots , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[13]  Gaurav S. Sukhatme,et al.  Multi-Robot Task Allocation in Uncertain Environments , 2003, Auton. Robots.

[14]  Lovekesh Vig,et al.  Multi-robot coalition formation , 2006, IEEE Transactions on Robotics.

[15]  Sebastian Thrun,et al.  Robotic mapping: a survey , 2003 .

[16]  Wolfram Burgard,et al.  Coordinated multi-robot exploration , 2005, IEEE Transactions on Robotics.

[17]  Anthony Stentz,et al.  Complex Task Allocation For Multiple Robots , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[18]  Kurt Konolige,et al.  Distributed Multirobot Exploration and Mapping , 2005, Proceedings of the IEEE.

[19]  Emanuele Menegatti,et al.  Cooperation Issues and Distributed Sensing for Multirobot Systems , 2006, Proceedings of the IEEE.

[20]  Dale A. Carnegie,et al.  Applications of an adaptive hierarchical mobile robot navigation system , 2007 .

[21]  Anthony Stentz,et al.  Multi-robot exploration controlled by a market economy , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[22]  Anthony Stentz,et al.  Opportunistic optimization for market-based multirobot control , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Daniele Nardi,et al.  Multirobot systems: a classification focused on coordination , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[24]  Maja J. Mataric,et al.  Broadcast of Local Elibility for Multi-Target Observation , 2000, DARS.

[25]  Maja J. Mataric,et al.  Sold!: auction methods for multirobot coordination , 2002, IEEE Trans. Robotics Autom..

[26]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[27]  Sarit Kraus,et al.  Methods for Task Allocation via Agent Coalition Formation , 1998, Artif. Intell..

[28]  Howie Choset,et al.  Coverage for robotics – A survey of recent results , 2001, Annals of Mathematics and Artificial Intelligence.

[29]  Anthony Stentz,et al.  TraderBots : a market-based approach for resource, role, and task allocation in multirobot coordination , 2003 .

[30]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[31]  Manuela M. Veloso,et al.  Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork , 1999, Artif. Intell..

[32]  Lovekesh Vig,et al.  Market-Based Multi-robot Coalition Formation , 2006, DARS.

[33]  Hsiu-Hui Lee,et al.  Multi-Agent Coalition Formation for Long-Term Task or Mobile Network , 2006, 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06).

[34]  Hans P. Moravec.  Sensor Fusion in Certainty Grids for Mobile Robots , 1988, AI Mag..

[35]  Judea Pearl,et al.  Heuristics : intelligent search strategies for computer problem solving , 1984 .