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Market-Based Multirobot Coordination: A Survey and Analysis
, 2006
"... When robots work together as a team, the members that perform each task should be the ones that promise to use the least resources to do the job. ..."
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Cited by 225 (5 self)
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When robots work together as a team, the members that perform each task should be the ones that promise to use the least resources to do the job.
Issues in multi-robot coalition formation
- IN PROC. MULTI-ROBOT SYST. FROM SWARMS TO INTELL. AUTOMATA
, 2006
"... As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in ..."
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Cited by 66 (4 self)
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As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in both super additive and non-super additive environments. The algorithmic techniques vary from negotiation-based protocols in multi-agent system (MAS) environments to those based on computation in distributed problem solving (DPS) environments. Coalition formation behaviors have also been discussed in relation to game theory. Despite the plethora of MAS coalition formation literature, to the best of our knowledge none of the proposed algorithms have been demonstrated with an actual multi-robot system. There exists a discrepancy between the multi-agent algorithms and their applicability to the multi-robot domain. This paper aims to bridge that discrepancy by unearthing the issues that arise while attempting to tailor these algorithms to the multi-robot domain. A well-known multi-agent coalition formation algorithm has been studied in order to identify the necessary modifications to facilitate its application to the multi-robot domain. This paper reports multi-robot coalition formation results based upon simulation and actual robot experiments. A multi-agent coalition formation algorithm has been demonstrated on an actual robot system.
Dynamically Formed Heterogeneous Robot Teams Performing Tightly-Coordinated Tasks
- Proceedings of the International Conference on Robotics and Automation
, 2006
"... As we progress towards a world where robots play an integral role in society, a critical problem that remains to be solved is the Pickup Team challenge; that is, dynamically formed heterogeneous robot teams executing coordinated tasks where little information is known a-priori about the tasks, the r ..."
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Cited by 52 (8 self)
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As we progress towards a world where robots play an integral role in society, a critical problem that remains to be solved is the Pickup Team challenge; that is, dynamically formed heterogeneous robot teams executing coordinated tasks where little information is known a-priori about the tasks, the robots, and the environments in which they will operate. Successful solutions to forming pickup teams will enable researchers to experiment with larger numbers of robots and enable industry to efficiently and cost-effectively integrate new robot technology with existing legacy teams. In this paper, we define the challenge of pickup teams and propose the treasure hunt domain for evaluating the performance of pickup teams. Additionally, we describe a basic implementation of a pickup team that can search and discover treasure in a previously unknown environment. We build on prior approaches in market-based task allocation and Plays for synchronized task execution, to allocate roles amongst robots in the pickup team, and to execute synchronized team actions to accomplish the treasure hunt task.
A complete methodology for generating multi-robot task solutions using asymtre-d and market-based task allocation
- in: Proc of the IEEE Int Conf on Robotics and Automation
, 2007
"... Abstract — This paper presents an approach that enables heterogeneous robots to automatically form groups as needed to generate both strongly-cooperative and weakly-cooperative multi-robot task solutions in the same application. The fundamental contribution of this work is the layering of our lowlev ..."
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Cited by 20 (2 self)
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Abstract — This paper presents an approach that enables heterogeneous robots to automatically form groups as needed to generate both strongly-cooperative and weakly-cooperative multi-robot task solutions in the same application. The fundamental contribution of this work is the layering of our lowlevel coalition formation algorithm for generating stronglycooperative task solutions, with high-level, traditional task allocation methods for weakly-cooperative task solutions. At the low level, coalitions that generate strongly-cooperative multi-robot task solutions are formed using our ASyMTRe-D approach that maps environmental sensors and perceptual and motor schemas to the required flow of information in the robot team, automatically reconfiguring the connections of schemas within and across robots to form efficient solutions. At the high level, a traditional task allocation approach is used to enable individual robots and/or coalitions to compete for weakly-cooperative task assignments through task allocation. We introduce the site clearing task to motivate the work, and then formalize the problem. We then present the approach of layering ASyMTRe-D with task allocation. We validate the approach on a team of robots with the site clearing task. We believe the resulting approach is a flexible system that can handle a broad range of realistic multi-robot applications beyond what is possible using other existing approaches. I.
Coalition Formation: From Software Agents to Robots
- J INTELL ROBOT SYST (2007) 50:85–118
, 2007
"... A problem that has recently attracted the attention of the research community is the autonomous formation of robot teams to perform complex multirobot tasks. The corresponding problem for software agents is also known in the multi-agent community as the coalition formation problem. Numerous algorith ..."
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Cited by 20 (0 self)
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A problem that has recently attracted the attention of the research community is the autonomous formation of robot teams to perform complex multirobot tasks. The corresponding problem for software agents is also known in the multi-agent community as the coalition formation problem. Numerous algorithms for software agent coalition formation have been provided that allow for efficient cooperation in both competitive and cooperative environments. However, despite the plethora of relevant literature on the software agent coalition formation problem, and the existence of similar problems in theoretical computer science, the multirobot coalition formation problem has not been sufficiently grounded for different tasks and task environments. In this paper, comparisons are drawn to highlight the differences between software agents and robotics, and parallel problems from theoretical computer science are identified. This paper further explores robot coalition formation in different practical robotic environments. A heuristic-based coalition formation algorithm from our previous work was extended to operate in precedence ordered cooperative environments. In order to explore coalition formation in competitive environments, the paper also studies the RACHNA system, a market based coalition formation system. Finally, the paper investigates the notion of task preemption for complex multi-robot tasks in random allocation environments.
SET: An algorithm for distributed multirobot task allocation with dynamic negotiation based on task subsets
- IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
, 2007
"... ..."
Market-based multi-robot coalition formation
"... Summary. Task allocation is an issue that every multi-robot system must address. Recent task allocation solutions propose an auction based approach wherein robots bid for tasks based on cost functions for performing a task. This paper presents RACHNA, a novel architecture for multi-robot task alloca ..."
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Cited by 11 (1 self)
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Summary. Task allocation is an issue that every multi-robot system must address. Recent task allocation solutions propose an auction based approach wherein robots bid for tasks based on cost functions for performing a task. This paper presents RACHNA, a novel architecture for multi-robot task allocation based on a modified algorithm for the winner determination problem in multi-unit combinatorial auctions. A more generic utility based framework is proposed to accommodate different types of tasks and task environments. Preliminary experiments yield promising results demonstrating the system’s superiority over simple task allocation techniques. 1
Multi-Agent Role Allocation: Issues, Approaches, and Multiple Perspectives
- AUTON AGENT MULTI-AGENT SYST
"... In cooperative multi-agent systems, roles are used as a design concept when creating large systems, they are known to facilitate specialization of agents, and they can help to reduce interference in multi-robot domains. The types of tasks that the agents are asked to solve and the communicative capa ..."
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Cited by 11 (0 self)
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In cooperative multi-agent systems, roles are used as a design concept when creating large systems, they are known to facilitate specialization of agents, and they can help to reduce interference in multi-robot domains. The types of tasks that the agents are asked to solve and the communicative capabilities of the agents significantly affect the way roles are used in cooperative multi-agent systems. Along with a discussion of these issues about roles in multi-agent systems, this article compares computational models of the role allocation problem, presents the notion of explicitly versus implicitly defined roles, gives a survey of the methods used to approach role allocation problems, and concludes with a list of open research questions related to roles in multi-agent systems.
Dynamic redistribution of a swarm of robots among multiple sites
- in Proc. Int’l. Conf. on Intelligent Robots and Systems (IROS
"... Abstract — We present an approach for the dynamic assign-ment and reassignment of a large team of homogeneous robotic agents to multiple locations with applications to search and rescue, reconnaissance and exploration missions. Our work is inspired by experimental studies of ant house hunting and em ..."
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Cited by 11 (5 self)
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Abstract — We present an approach for the dynamic assign-ment and reassignment of a large team of homogeneous robotic agents to multiple locations with applications to search and rescue, reconnaissance and exploration missions. Our work is inspired by experimental studies of ant house hunting and empirical models that predict the behavior of the colony that is faced with a choice between multiple candidate nests. We design stochastic control policies that enable the team of agents to distribute themselves between multiple candidate sites in a specified ratio. Additionally, we present an extension to our model to enable fast convergence via switching behaviors based on quorum sensing. The stability and convergence properties of these control policies are analyzed and simulation results are presented. I.
