Stochastic strategies for a swarm robotic assembly system

Matthey, Löıc; Berman, Spring; Kumar, Vijay

doi:10.1109/robot.2009.5152457

Cited by 67 publications

(48 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stochastic and distributed control of swarms of robots was extensively studied by Kumar and colleagues [59], who also exploit modeling methods originating from the study of chemical systems [60]. The chemical formalism well suits the description of SA, as will be shown in Sections 3.1 and 4.1 and as further demonstrated in recent studies involving real and simulated robots [61,62].…”

Section: Self-assembly Of Small Modular Robotsmentioning

confidence: 96%

Modeling Self-Assembly Across Scales: The Unifying Perspective of Smart Minimal Particles

2011

View full text Add to dashboard Cite

A wealth of current research in microengineering aims at fabricating devices of increasing complexity, notably by (self-)assembling elementary components into heterogeneous functional systems. At the same time, a large body of robotic research called swarm robotics is concerned with the design and the control of large ensembles of robots of decreasing size and complexity. This paper describes the asymptotic convergence of micro/nano electromechanical systems (M/NEMS) on one side, and swarm robotic systems on the other, toward a unifying class of systems, which we denote Smart Minimal Particles (SMPs). We define SMPs as mobile, purely reactive and physically embodied agents that compensate for their limited on-board capabilities using specifically engineered reactivity to external physical stimuli, including local energy and information scavenging. In trading off internal resources for simplicity and robustness, SMPs are still able to collectively perform non-trivial, spatio-temporally coordinated and highly scalable operations such as aggregation and self-assembly (SA). We outline the opposite converging tendencies, namely M/NEMS smarting and robotic minimalism, by reviewing each field's literature with specific focus on self-assembling systems. Our main claim is that the SMPs can be used to develop a unifying technological and methodological framework that bridges the gap between passive M/NEMS and active, centimeter-sized robots. By proposing this unifying perspective, we hypothesize a continuum in both complexity and length scale between these two extremes. We illustrate the benefits of possible cross-fertilizations among these originally separate domains, with specific emphasis on the modeling OPEN ACCESS

show abstract

Section: Self-assembly Of Small Modular Robotsmentioning

confidence: 96%

Modeling Self-Assembly Across Scales: The Unifying Perspective of Smart Minimal Particles

2011

View full text Add to dashboard Cite

show abstract

“…A simple distributed 3D construction algorithm is described in [16], while [6] describes a 3D construction algorithm for modular blocks in a distributed setting. Stochastic algorithms for robotic construction with dependency on raw materials are analyzed in [7]. Our previous work on robotic construction includes Shady3D [9] utilizing a passive bar and an optimal algorithm for reconfiguration of a given truss structure to a target structure [8], and experiments in building truss structures [4].…”

Section: A Related Workmentioning

confidence: 99%

Constraint-aware coordinated construction of generic structures

Stein

Schoen

Rus

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

Abstract-This paper presents a constraint-aware decentralized approach to construction with teams of robots. We present an extension to existing work on a distributed controller for robotic construction of simple structures. Our previous work described a set of adaptive algorithms for constructing truss structures given a target geometry using continuous and graph-based equal-mass partitioning [1], [2]. Using this work as a foundation, we present an algorithm which performs construction tasks and conforms to physical constraints while considering those constraints to parallelize tasks. This is accomplished by defining a mass function which reflects the priority of part placement and prevents physically impossible states. This mass function generates a set of pointmasses in R n , and we present a novel algorithm for finding a locally optimal, equalmass, convex tessellation of such a set.

show abstract

“…Previous attempts to use CRNs and biochemical modeling in robotics have been very successful [15]- [17]. Klavins and colleagues have used a similar framework for building a stochastic interpretation of their graph grammars [14].…”

Section: State Of the Artmentioning

confidence: 99%

Comparing and modeling distributed control strategies for miniature self-assembling robots

Evans

Mermoud

Martinoli

2010

2010 IEEE International Conference on Robotics and Automation

View full text Add to dashboard Cite

Abstract-We propose two contrasting approaches to the scalable distributed control of a swarm of self-assembling miniaturized robots, specifically the formation of chains of a desired length: (1) a deterministic controller in which robots communicate with each other in order to directly limit the size of each chain, and (2) a probabilistic controller where the average chain size is controlled by the probability a robot will choose to leave its chain. We demonstrate the feasibility of both approaches by implementing them on a real swarm of Alice robots. Using Webots, a realistic simulator for mobile robotics, and macroscopic models based on the Chemical Reaction Network (CRN) framework, we investigate the limitations of the deterministic controller and demonstrate the existence of optimal parameters for the probabilistic controller where exploration and exploitation are well balanced, thus favoring the formation of larger chains.

show abstract

Stochastic strategies for a swarm robotic assembly system

Cited by 67 publications

References 16 publications

Modeling Self-Assembly Across Scales: The Unifying Perspective of Smart Minimal Particles

Modeling Self-Assembly Across Scales: The Unifying Perspective of Smart Minimal Particles

Constraint-aware coordinated construction of generic structures

Comparing and modeling distributed control strategies for miniature self-assembling robots

Contact Info

Product

Resources

About