Information invariants for distributed manipulation
International Journal of Robotics Research
Traderbots: a new paradigm for robust and efficient multirobot coordination in dynamic environments
Traderbots: a new paradigm for robust and efficient multirobot coordination in dynamic environments
Coalition Formation: From Software Agents to Robots
Journal of Intelligent and Robotic Systems
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
Methods for task allocation via agent coalition formation
Artificial Intelligence
Multi-robot coalition formation
IEEE Transactions on Robotics
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Multi-objective robot coalition formation for non-additive environments
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part I
Development of a reduced human user input task allocation method for multiple robots
Robotics and Autonomous Systems
A decision network based framework for multiagent coalition formation
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
A comprehensive taxonomy for multi-robot task allocation
International Journal of Robotics Research
Towards a robust feedback system for coordinating a hierarchical multi-robot system
Robotics and Autonomous Systems
Non-additive multi-objective robot coalition formation
Expert Systems with Applications: An International Journal
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In multi-robot systems, task allocation and coordination are two fundamental problems that share high synergy. Although multi-robot architectures typically separate them into distinct layers, relevant improvementmay be expected from solutions that are able to concurrently handle them at the same "level". This paper proposes a novel framework, called CoMutaR (Coalition formation based onMultitasking Robots), which is used for both tackle task distribution among teams of mobile robots, and to guarantee the coordination within the formed teams. Robot capabilities are modelled as actions, independent modules whose inputs do not depend on the robot that generated it. Solutions to tasks are devised as coalitions of actions, that can be spread amongst the available robots. We also define the concept of share-restricted resources, which are periodically checked and updated by the actions in the system. In contrast to prior approaches, this mechanism enables to quickly determine if two actions can be executed simultaneously, allowing a single robot to execute multiple tasks concurrently. A single-round auction protocol is used to automatically discover and form coalitions. Once a coalition is formed, coordination among robots is modelled as constraints imposed over the share-restricted resources. Finally, we have successfully implemented and applied CoMutaR in typical scenarios like object transportation, area surveillance, and multi-robot box pushing. Experimental results demonstrate that the system is able to provide good solutions even in the case of severe failures in participating robots.