Programming modular robots with locally distributed predicates

Rosa, Michael De; Goldstein, Seth Copen; Lee, P.; Pillai, Padmanabhan; Campbell, Jason

doi:10.1109/robot.2008.4543691

Cited by 43 publications

(26 citation statements)

References 14 publications

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“…Meld was designed for modular robots where the inter-robot communication is limited to immediate neighbors. Locally distributed predicates [5] are distributed conditions that hold for a connected ensemble of the robotic system. Programs in this paradigm are collection of LDPs with actions that are triggered when subensembles match a particular predicate.…”

Section: Related Workmentioning

confidence: 99%

Programming micro-aerial vehicle swarms with karma

Dantu

Kate

Waterman

et al. 2011

Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems

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Research in micro-aerial vehicle (MAV) construction, control, and high-density power sources is enabling swarms of MAVs as a new class of mobile sensing systems. For efficient operation, such systems must adapt to dynamic environments, cope with uncertainty in sensing and control, and operate with limited resources. We propose a novel system architecture based on a hive-drone model that simplifies the functionality of an individual MAV to a sequence of sensing and actuation commands with no in-field communication. This decision simplifies the hardware and software complexity of individual MAVs and moves the complexity of coordination entirely to a central hive computer. We present Karma, a system for programming and managing MAV swarms. Through simulation and testbed experiments we demonstrate how applications in Karma can run on limited resources, are robust to individual MAV failure, and adapt to changes in the environment.

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Section: Related Workmentioning

confidence: 99%

Programming micro-aerial vehicle swarms with karma

Dantu

Kate

Waterman

et al. 2011

Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems

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“…The question we seek to answer is what price does one pay, if any, for this added generality? In this paper, we compare these approaches to scalable shape change, using LDP [3], a system for concisely representing distributed programs for MRRs. As part of this study we illustrate the capability of LDP to enable rapid and concise …”

Section: Mrrs and Motion Planningmentioning

confidence: 99%

“…By abstracting such concerns as variable storage, consistency, and messaging, LDP allows programmers to concentrate on the details of their particular distributed algorithm, rather than on support code. A brief overview of LDP's syntax and operation is presented beginning in Section II-A, with more extensive treatment of the language and runtime having been presented in [3]. .…”

Section: Locally Distributed Predicatesmentioning

confidence: 99%

A tale of two planners: Modular robotic planning with LDP

Rosa

Goldstein

Lee

et al. 2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-LDP (Locally Distributed Predicates) is a distributed, high-level language for programming modular reconfigurable robot systems (MRRs). In this paper we present the implementation of two motion-planning algorithms in LDP, and analyze both their performance and ease of implementation. We present multiple variations of one planner, including a novel resource allocation algorithm. We then draw conclusions about both the utility of the motion-planning algorithms and the suitability of LDP to the problem space. Our experiments suggest that metamodule-based planning approaches have a cost in time and/or energy terms, but that the cost can be worth paying in exchange for the additional generality and separationof-concerns offered by these techniques. The particular tradeoff for a given system will depend upon its goals and the details of the underlying modules. I. MRRS AND MOTION PLANNINGThe problem of reconfiguration / shape planning for modular robotic systems (MRRs) presents several challenges over and above those found in non-modular robots. The large number of discrete modules results in a correspondingly large number of degrees of freedom, and creates a very large state space that a planner may have to explore. Furthermore, the motions of individual modules are often restricted in non-trivial ways, e.g., moving a module to an adjacent empty space may require many other modules to move out of the way due to blocking constraints. Essentially, two configurations that are similar in state space, may actually be separated by a long reconfiguration path.Two recent approaches attempt to overcome blocking constraints and allow scalable, disconnection-free, stochastic planning in large MRRs. A scaffold-based technique [1] restricts modules to a specific grid structure that allows other modules to pass through unhindered. More recent work [2] groups modules together into metamodules and provides a high-level set of primitives that are not subject to blocking constraints. Both allow greedy or stochastic shape planning to succeed. However, the metamodule system is more general, and can be implemented on a variety of different MRR designs. The question we seek to answer is what price does one pay, if any, for this added generality? In this paper, we compare these approaches to scalable shape change, using LDP [3], a system for concisely representing distributed programs for MRRs. As part of this study we illustrate the capability of LDP to enable rapid and concise A. The Shape Change ProblemThe shape change problem considered in this paper is the reconfiguration of a large lattice-style MRR from a starting shape to a target shape. We assume that the system is provided with a target shape (e.g., list of desired module positions, variably-sized blocks [1], or isosurface equations). Furthermore, we assume that the modules are aware of their locations in the initial shape, either through a-priori knowledge (e.g. from the structure of the lattice), or from a localization algorithm [4], [5].All communication within large ...

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“…A common approach to tackle mobility has not materialized yet; most of the research efforts are focused on the scalability aspect, in particular, the need to program the network as a whole rather than as an individual set of nodes [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

ASH: Tackling Node Mobility in Large-Scale Networks

Pruteanu

Dulman

Langendoen

2010

2010 Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems

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Abstract-With an increased adoption of technologies like wireless sensor networks by real-world applications, dynamic network topologies are becoming the rule rather than the exception. Node mobility, however, introduces a range of problems (communication interference, path uncertainty, low quality of service and information loss, etc.) that are not handled well by periodically refreshing state information, as algorithms designed for static networks typically do. The main contribution of this paper is the introduction of a novel mechanism (called ASH) for the creation of a quasi-static overlay on top of a mobile topology. It is powered by simple, local interactions between nodes and exhibits selfhealing and self-organization capabilities with respect to failures and node mobility. We show that the overlay mechanism works without assumptions about position, orientation, speed, motion correlation, and trajectory prediction of the nodes. A preliminary evaluation by means of simulation shows that ASH succeeds in tackling node mobility, while consuming only minimal resources.

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Programming modular robots with locally distributed predicates

Cited by 43 publications

References 14 publications

Programming micro-aerial vehicle swarms with karma

Programming micro-aerial vehicle swarms with karma

A tale of two planners: Modular robotic planning with LDP

ASH: Tackling Node Mobility in Large-Scale Networks

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