Design of ant-inspired stochastic control policies for collective transport by robotic swarms

Wilson, Sean; Pavlic, Theodore P.; Kumar, Ganesh P.; Buffin, Aurélie; Pratt, Stephen C.; Berman, Spring

doi:10.1007/s11721-014-0100-8

Cited by 52 publications

(21 citation statements)

References 35 publications

(57 reference statements)

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“…Toward this end, we will implement local wireless communication on the robots and the ability to autonomously recharge. In collective transport experiments, we will replace the centralized planning of robot trajectories with a boundary coverage scheme such as our stochastic strategy in [27] to achieve robot allocation around a load. The robots will use consensus algorithms to coordinate their grasping, lifting, and transport of the load, rather than relying on external commands to synchronize these actions.…”

Section: Discussionmentioning

confidence: 99%

Pheeno, A Versatile Swarm Robotic Research and Education Platform

Wilson

Gameros

Sheely

et al. 2016

IEEE Robot. Autom. Lett.

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Abstract-Swarms of low-cost autonomous robots can potentially be used to collectively perform tasks over very large domains and time scales. Novel robots for swarm applications are currently being developed as a result of recent advances in sensing, actuation, processing, power, and manufacturing. These platforms can be used by researchers to conduct experiments with robot collectives and by educators to include robotic hardware in their curricula. However, existing low-cost robots are specialized and can lack desired sensing, navigation, control, and manipulation capabilities. This paper presents a new mobile robot platform, Pheeno, that is affordable, versatile, and suitable for multi-robot research, education, and outreach activities. Users can modify Pheeno for their applications by designing custom modules that attach to its core module. We describe the design of the Pheeno core and a three degree-of-freedom gripper module, which enables unprecedented manipulation capabilities for a robot of Pheeno's size and cost. We experimentally demonstrate Pheeno's ability to fuse measurements from its onboard odometry for global position estimation and use its camera for object identification in real time. We also show that groups of two and three Pheenos can act on commands from a central controller and consistently transport a payload in a desired direction.

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Section: Discussionmentioning

confidence: 99%

Pheeno, A Versatile Swarm Robotic Research and Education Platform

Wilson

Gameros

Sheely

et al. 2016

IEEE Robot. Autom. Lett.

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“…Coating has been extensively studied in the area of swarm robotics, but not commonly treated as a stand-alone problem; it is instead examined as part of collective transport (e.g., [11]) or collective perception (e.g., see respective section of [12]). Some research focuses on coating objects as an independent task under the name of target surrounding or boundary coverage.…”

Section: Related Workmentioning

confidence: 99%

On the Runtime of Universal Coating for Programmable Matter

Derakhshandeh

Gmyr

Porter

et al. 2016

Lecture Notes in Computer Science

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Abstract. Imagine coating buildings and bridges with smart particles (also coined smart paint) that monitor structural integrity and sense and report on traffic and wind loads, leading to technology that could do such inspection jobs faster and cheaper and increase safety at the same time. In this paper, we study the problem of uniformly coating objects of arbitrary shape in the context of self-organizing programmable matter, i.e., programmable matter which consists of simple computational elements called particles that can establish and release bonds and can actively move in a self-organized way. Particles are anonymous, have constant-size memory, and utilize only local interactions in order to coat an object. We continue the study of our Universal Coating algorithm by focusing on its runtime analysis, showing that our algorithm terminates within a linear number of rounds with high probability. We also present a matching linear lower bound that holds with high probability. We use this lower bound to show a linear lower bound on the competitive gap between fully local coating algorithms and coating algorithms that rely on global information, which implies that our algorithm is also optimal in a competitive sense. Simulation results show that the competitive ratio of our algorithm may be better than linear in practice.

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“…One of the tasks groups of some ants pieces must complete is cooperative transport -the movement of large objects such as food items, intact, by multiple individuals (18). This is an interesting task for coordination research because it is prone to deadlocks, and has direct applications in robotics (4,(19)(20)(21)(22). A major challenge for cooperative transport is that the individuals must move the object the same direction.…”

Section: Introductionmentioning

confidence: 99%

Consensus or deadlock? Consequences of simple behavioral rules for coordination in group decisions

McCreery

Correll

Breed

et al. 2016

Preprint

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Coordinated collective behaviors often emerge from simple rules governing the interactions of individuals in groups. We model mechanisms of coordination among ants during cooperative transport, a challenging task that requires a consensus on travel direction. Our goal is to determine whether groups following simple behavioral rules can reach a consensus using minimal information. Using deterministic and stochastic models, we investigate behavioral factors that affect coordination. We define and investigate three types of behavioral rules governing individual behavior that differ in the information available: individuals either 1) have no information, 2) can measure transport success, or 3) measure success while also knowing whether they are aligned with the majority. We find that groups break deadlocks only if individuals more readily give up when they are going against the majority, corresponding to rule type 3 -such groups are "informed." These behavioral rules succeed through positive and negative feedbacks that are implemented in our model via a single mechanism: individuals only need to measure the relative group sizes to make effective decisions. We also find that groups reach consensus more quickly if they have either a shared bias, high sensitivity to group behavior, or finely tuned persistence. Each of these is a potential adaptation for efficient cooperative transport. This flexibility makes the behavioral rules in the informed case relatively robust to deficiencies in the individuals' capabilities. While inspired by ants, our results are generalizable to other collective decisions with deadlocks, and demonstrate that groups of behaviorally simple individuals with no memory and extremely limited information can break symmetry and reach a consensus in a decision between two equal options.

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Design of ant-inspired stochastic control policies for collective transport by robotic swarms

Cited by 52 publications

References 35 publications

Pheeno, A Versatile Swarm Robotic Research and Education Platform

Pheeno, A Versatile Swarm Robotic Research and Education Platform

On the Runtime of Universal Coating for Programmable Matter

Consensus or deadlock? Consequences of simple behavioral rules for coordination in group decisions

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