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48
Distributed intelligence: Overview of the field and its application in multi-robot systems
- Journal of Physical Agents
, 2008
"... Abstract—This article overviews the concepts of distributed intelligence, outlining the motivations for studying this field of research. First, common systems of distributed intelligence are classified based upon the types of interactions exhibited, since the type of interaction has relevance to the ..."
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Cited by 37 (1 self)
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Abstract—This article overviews the concepts of distributed intelligence, outlining the motivations for studying this field of research. First, common systems of distributed intelligence are classified based upon the types of interactions exhibited, since the type of interaction has relevance to the solution paradigm to be used. We outline three common paradigms for distributed intelligence — the bioinspired paradigm, the organizational and social paradigm, and the knowledge-based, ontological paradigm — and give examples of how these paradigms can be used in multi-robot systems. We then look at a common problem in multirobot systems — that of task allocation — and show how the solution approach to this problem is very different depending upon the paradigm chosen for abstracting the problem. Our conclusion is that the paradigms are not interchangeable, but rather the selection of the appropriate paradigm is dependent
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.
Cooperation of heterogeneous, autonomous robots: A case study of humanoid and wheeled robots
- In Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS
, 2007
"... Abstract — In this paper we present a case study of cooperation of a strongly heterogeneous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some competing capabilities. By combining two strongly heterogeneous robots the diversity of acco ..."
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Cited by 5 (4 self)
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Abstract — In this paper we present a case study of cooperation of a strongly heterogeneous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some competing capabilities. By combining two strongly heterogeneous robots the diversity of accomplishable tasks increases as the variety of sensors and actuators in the robot systems is extended compared with a team consisting of homogeneous robots. The scenario describes a tightly cooperative task, where the humanoid robot and the wheeled robot follow for a long distance a ball, which is kicked finally by the humanoid robot into a goal. The task can be fulfilled successfully by combining the abilities of both robots. For task distribution and allocation, a newly developed objective function is presented which is based on a proper modeling of the sensing, perception, motion and onboard computing
Model-Based Relative Localization for Cooperative Robots Using Stereo Vision
"... In the last years, Multi-Robot Systems (MRS) have been receiving great attention, as they can be effectively employed in several fields. Generally, for a collaborative behaviour to be successful, a precise localization strategy is required. A number of collective positioning schemes are available in ..."
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Cited by 4 (0 self)
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In the last years, Multi-Robot Systems (MRS) have been receiving great attention, as they can be effectively employed in several fields. Generally, for a collaborative behaviour to be successful, a precise localization strategy is required. A number of collective positioning schemes are available in literature, which mainly differ depending on the sensors and on the cooperation strategies adopted. In this work, we propose a model-based relative localization method using stereo vision, which enables a complex agent, equipped with a stereo head, to simultaneously detect and localize several small robots, navigating in a coordinated manner for a common task. The paper describes the method in detail and presents experimental tests performed on a real multi-agent system, proving the method to be accurate and effective for multi-robot localization, and environment exploration and mapping. 1
Towards Cooperation of Heterogeneous, Autonomous Robots: A Case Study of Humanoid and Wheeled Robots
, 2010
"... In this paper a case study of cooperation of a strongly heterogeneous autonomous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some redundant abilities is presented. By combining strongly heterogeneous robots the diversity of achievabl ..."
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Cited by 3 (0 self)
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In this paper a case study of cooperation of a strongly heterogeneous autonomous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some redundant abilities is presented. By combining strongly heterogeneous robots the diversity of achievable tasks increases as the variety of sensing and motion abilities of the robot system is extended compared to a usually considered team of homogeneous robots. A number of methodologies and technologies required to achieve the long-term goal of cooperation of heterogeneous autonomous robots are discussed including modeling tasks and robot abilities, task assignment and redistribution, robot behavior modeling and programming, robot middleware and robot simulation. Example solutions and their application to the cooperation of autonomous wheeled and humanoid robots are presented in this case study. The scenario describes a tightly coupled cooperative task, where the humanoid robot and the wheeled robot track a moving ball, which is to be approached and kicked by the humanoid robot into a goal. The task can be fulfilled successfully by combining the abilities of both robots.
MULTIPLE ROBOT GRAPH EXPLORATION
, 2007
"... This report investigates the problem of exploration and mapping in an embedded graph-like world. Graph-like worlds provide a useful theoretical model within which to explore fundamental limits to exploration and mapping. It is demonstrated that a collec-tion of identical robots, each equipped with i ..."
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Cited by 2 (2 self)
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This report investigates the problem of exploration and mapping in an embedded graph-like world. Graph-like worlds provide a useful theoretical model within which to explore fundamental limits to exploration and mapping. It is demonstrated that a collec-tion of identical robots, each equipped with its own unique marker can explore and map an unknown graph-like environment. Developing such an algorithm addresses fundamen-tal issues related to multiple-robot exploration, i.e., location disambiguation, merging partial world representations obtained by multiple robots, partitioning the exploration task, and rendezvous scheduling. ii
Affective Task Allocation for Distributed Multi-Robot Teams
, 2004
"... This article presents a novel emotion-based recruitment approach to the multi-robot task allocation problem. This approach requires less communication bandwidth than auction methods, enabling it to scale to large team sizes, and making it appropriate for low-power or stealth applications. Affective ..."
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Cited by 2 (0 self)
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This article presents a novel emotion-based recruitment approach to the multi-robot task allocation problem. This approach requires less communication bandwidth than auction methods, enabling it to scale to large team sizes, and making it appropriate for low-power or stealth applications. Affective recruitment is tolerant of unreliable communications channels, and can find better solutions than simple greedy schedulers (based on experimental metrics of the time necessary to complete recruitment and the total number of messages transmitted). Experimental results in simulation and on three UGVs and one UAV in a mine-detection task show that affective recruitment succeeds with network failure rates up to 25% and requires 32% fewer transmissions compared to existing methods on average. Affective recruitment also scales better with team size, requiring up to 61% fewer transmissions than a greedy instantaneous scheduler that has an O(n) communications complexity, without a significant increase in allocation time.
Wireless communications for distributed navigation in robot swarms
"... Abstract. We consider a swarm of robots equipped with an infrared range and bearing device that is able both to make estimates of the relative distance and angle between two robots in line-of-sight and to transfer data between them. Through the infrared range and bearing device, the robots create a ..."
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Abstract. We consider a swarm of robots equipped with an infrared range and bearing device that is able both to make estimates of the relative distance and angle between two robots in line-of-sight and to transfer data between them. Through the infrared range and bearing device, the robots create a line-of-sight mobile ad hoc network. We investigate different ways to implement a swarm-level distributed navigation function exploiting the routing information gathered within this network. In the scenario we consider, a number of different events present themselves in different locations. To be serviced, each event requires that a robot with the appropriate skills comes to its location. We present two swarm-level solutions for guiding the navigation of the selected robots towards the events. We use a bio-inspired ad hoc network routing protocol to dynamically find and maintain paths between a robot and an event location in the mobile line-of-sight network, and use them to guide the robot to its goal. The performance of the two approaches is studied in a number of network scenarios presenting different density, mobility, and bandwidth availability. 1
Robot Navigation in a Networked Swarm
, 2008
"... problems with objective function of increasing complexity ” and by the SWARMANOID project, funded by the ..."
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problems with objective function of increasing complexity ” and by the SWARMANOID project, funded by the
Hybrid Control for Large Swarms of Aquatic Drones
"... Maritime tasks, such as surveillance and patrolling, aqua-culture inspection, and wildlife monitoring, typically require large operational crews and expensive equipment. Only re-cently have unmanned vehicles started to be used for such missions. These vehicles, however, tend to be expensive and have ..."
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Maritime tasks, such as surveillance and patrolling, aqua-culture inspection, and wildlife monitoring, typically require large operational crews and expensive equipment. Only re-cently have unmanned vehicles started to be used for such missions. These vehicles, however, tend to be expensive and have limited coverage, which prevents large-scale deploy-ment. In this paper, we propose a scalable robotics system based on swarms of small and inexpensive aquatic drones. We take advantage of bio-inspired artificial evolution tech-niques in order to synthesize scalable and robust collective behaviors for the drones. The behaviors are then combined hierarchically with preprogrammed control in an engineered-centric approach, allowing the overall behavior for a particu-lar mission to be quickly configured and tested in simulation before the aquatic drones are deployed. We demonstrate the scalability of our hybrid approach by successfully deploying up to 1,000 simulated drones to patrol a 20 km long strip for 24 hours.
