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We present the Pluggable Distributed Resource Allocator (PDRA), a middlewarefor distributed computing in heterogeneous mobile robotic networks. PDRAenables autonomous robotic agents to share computational resources forcomputationally expensive tasks such as localization and path planning. It sitsbetween an existing single-agent planner/executor and existing computationalresources (e.g. ROS packages), intercepts the executor's requests and, ifneeded, transparently routes them to other robots for execution. PDRA ispluggable: it can be integrated in an existing single-robot autonomy stack withminimal modifications. Task allocation decisions are performed by amixed-integer programming algorithm, solved in a shared-world fashion, thatmodels CPU resources, latency requirements, and multi-hop, periodic,bandwidth-limited network communications; the algorithm can minimize overallenergy usage or maximize the reward for completing optional tasks. Simulationresults show that PDRA can reduce energy and CPU usage by over 50% inrepresentative multi-robot scenarios compared to a naive scheduler; runs onembedded platforms; and performs well in delay- and disruption-tolerantnetworks (DTNs). PDRA is available to the community under an open-sourcelicense.

The Pluggable Distributed Resource Allocator (PDRA): a Middleware for Distributed Computing in Mobile Robotic Networks