Development of a multiagent robotic system with application to space exploration

Earon, Ernest J. P.; Barfoot, Timothy D.; D’Eleuterio, Gabriele M. T.

doi:10.1109/aim.2001.936902

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…While collaboration may be essential for some tasks, we are interested in studying tasks that can be done by a single robot, but where using multiple robots can potentially increase performance by decreasing the time to complete the task and/or by increasing the reliability. Sample tasks include mapping a large area [Thrun, 2001], placing a distributed sensor network [Earon et al, 2001], and cleaning up trash [Parker, 1996].…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of a Multi-Robot Search & Retrieval System: Experiences with MinDART

Rybski

Larson

Veeraraghavan

et al. 2008

J Intell Robot Syst

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The costs of developing mobile robot teams can be reduced if they are designed to exploit swarm techniques. In this methodology many simple homogeneous units solve complex tasks through emergent behavior. The challenge lies in selecting an appropriate control strategy for the individual units. Complexity in design costs both money and time, therefore a control strategy should be just complex enough to perform the task successfully in a variety of environments, relative to some performance measure. To explore the effects of control strategies and environmental factors on performance, we have conducted two sets of foraging experiments using real robots (the Minnesota Distributed Autonomous Robotic Team). The first set of experiments tested the efficacy of localization capabilities, in addition to the effects of team size and target distribution. The second set tested the efficacy of communication. We found that more complex control strategies do not necessarily improve task completion times, however they can reduce variance in performance measures. This can be valuable information for designers who need to assess the potential costs and benefits of increased complexity in design.

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Section: Related Workmentioning

confidence: 99%

Performance Evaluation of a Multi-Robot Search & Retrieval System: Experiences with MinDART

Rybski

Larson

Veeraraghavan

et al. 2008

J Intell Robot Syst

View full text Add to dashboard Cite

show abstract

“…By making the system modular and thus redundant, we could be willing to accept more risk in the design of a single robot because it no longer has the potential to produce a single point failure. In many of our early experiments, we tried designing controllers for our groups of robots by hand (Earon et al, 2001). This was possible for some simple tasks, such as having the robots position themselves in a particular geometric formation.…”

Section: A Solitary Ant Afield Cannot Be Considered To Have Much Ofmentioning

confidence: 99%

Evolutionary-Based Control Approaches for Multirobot Systems

Thangavelautham¹,

Barfoot²,

D’Eleuterio³

2008

Frontiers in Evolutionary Robotics

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“…The main motivation of collective robotics research is the coordination of several systems (Gerkey and Matarić, 2002;Agassounon et al, 2001;Melhuish, 1999;Flocchini et al, 2000) and the robustness that can be achieved by the redundancy of the whole system (Parker, 1998;Goldberg and Matarić, 2002;Fukuda et al, 1999). An increasing number of applications, such as space robotic missions (Chien et al, 2000;Earon et al, 2001) where there is a strong advantage in obtaining a more robust system, plan to exploit this type of information processing.…”

Section: Robustness To Hardware Failuresmentioning

confidence: 99%

“…Some researchers consider multiple rovers for all-terrain exploration (Chien et al, 2000;Earon et al, 2001) exploiting distributed hardware and, in some cases, distributed control to obtain a more robust system and better exploration performances 5 . To the best of the authors' knowledge, nobody has yet tried to take advantage of the collective aspect for obstacle climbing, except for some preliminary experiments using the modified version of Millibot mentioned earlier.…”

Section: Rough Terrain Navigationmentioning

confidence: 99%

Swarm-Bot: A New Distributed Robotic Concept

Pettinaro²,

et al. 2004

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Abstract. The swarm intelligence paradigm has proven to have very interesting properties such as robustness, flexibility and ability to solve complex problems exploiting parallelism and self-organization. Several robotics implementations of this paradigm confirm that these properties can be exploited for the control of a population of physically independent mobile robots.The work presented here introduces a new robotic concept called swarm-bot in which the collective interaction exploited by the swarm intelligence mechanism goes beyond the control layer and is extended to the physical level. This implies the addition of new mechanical functionalities on the single robot, together with new electronics and software to manage it. These new functionalities, even if not directly related to mobility and navigation, allow to address complex mobile robotics problems, such as extreme all-terrain exploration.The work shows also how this new concept is investigated using a simulation tool (swarmbot3d) specifically developed for quickly designing and evaluating new control algorithms. Experimental work shows how the simulated detailed representation of one s-bot has been calibrated to match the behaviour of the real robot.

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Development of a multiagent robotic system with application to space exploration

Cited by 12 publications

References 8 publications

Performance Evaluation of a Multi-Robot Search & Retrieval System: Experiences with MinDART

Performance Evaluation of a Multi-Robot Search & Retrieval System: Experiences with MinDART

Evolutionary-Based Control Approaches for Multirobot Systems

Swarm-Bot: A New Distributed Robotic Concept

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