Delirium: an embedding coordination language
Proceedings of the 1990 ACM/IEEE conference on Supercomputing
Distributed snapshots: determining global states of distributed systems
ACM Transactions on Computer Systems (TOCS)
Distributed Watchpoints: Debugging Large Modular Robot Systems
International Journal of Robotics Research
Detecting Locally Distributed Predicates
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Forty data communications research questions
ACM SIGCOMM Computer Communication Review
Detecting stable locality-aware predicates
Journal of Parallel and Distributed Computing
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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 separation-of-concerns offered by these techniques. The particular tradeoff for a given system will depend upon its goals and the details of the underlying modules.