Abstract
We consider the problem of assigning software processes (or tasks) to hardware processors in distributed robotics environments. We introduce the notion of a task variant, which supports the adaptation of software to specific hardware configurations. Task variants facilitate the trade-off of functional quality versus the requisite capacity and type of target execution processors. We formalise the problem of assigning task variants to processors as a mathematical model that incorporates typical constraints found in robotics applications; the model is a constrained form of a multi-objective, multi-dimensional, multiple-choice knapsack problem. We propose and evaluate three different solution methods to the problem: constraint programming, a constructive greedy heuristic and a local search metaheuristic. Furthermore, we demonstrate the use of task variants in a real instance of a distributed interactive multi-agent navigation system, showing that our best solution method (constraint programming) improves the system’s quality of service, as compared to the local search metaheuristic, the greedy heuristic and a randomised solution, by an average of 16, 31 and 56% respectively.
Highlights
Modern robotics systems are increasingly distributed, heterogeneous and collaborative, incorporating multiple independent agents that communicate via message passing and distributed protocols
We model the problem of task variant allocation in distributed robotics, in a general formulation that applies to the specifics of our case study
We have addressed a unique generalisation of the task allocation problem in distributed systems, with a specific application to robotics
Summary
Modern robotics systems are increasingly distributed, heterogeneous and collaborative, incorporating multiple independent agents that communicate via message passing and distributed protocols. Heterogeneity refers to the type and amount of hardware resources (e.g. sensors, CPU capacity) available on each agent in the system. In such systems, the efficient allocation of software processes (referred to as tasks) to hardware processors is of paramount importance in ensuring optimality. Previous works (Lee et al 2014; Liu and Shell 2012) generally take an approach that. This is one of several papers published in Autonomous Robots comprising the “Special Issue on Robotics Science and Systems”
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
