Resource-Performance Tradeoff Analysis for Mobile Robots
Morteza Lahijanian, María Svorenová, Akshay A. Morye, Brian Yeomans, Dushyant Rao, Ingmar Posner, Paul Newman, Hadas Kress-Gazit
Abstract
The design of mobile autonomous robots is challenging due to the limited on-board resources such as processing power and energy. A promising approach is to generate intelligent schedules that reduce the resource consumption while maintaining best performance, or more interestingly, to tradeoff reduced resource consumption for a slightly lower but still acceptable level of performance. In this letter, we provide a framework that is automatic and quantitative to aid designers in exploring such resource-performance tradeoffs and finding schedules for mobile robots, guided by questions such as “what is the minimum resource budget required to achieve a given level of performance?” The framework is based on a quantitative multiobjective verification technique, which, for a collection of possibly conflicting objectives, produces the Pareto front that contains all the achievable optimal tradeoffs. The designer then selects a specific Pareto point based on the resource constraints and desired performance level, and a correct-by-construction schedule that meets those constraints is automatically generated. We demonstrate the efficacy of this framework on several robotic scenarios in both simulations and experiments.
BibTeX
@inproceedings{ral2018_resourceperforma,
title = {Resource-Performance Tradeoff Analysis for Mobile Robots},
author = {Morteza Lahijanian and María Svorenová and Akshay A. Morye and Brian Yeomans and Dushyant Rao and Ingmar Posner and Paul Newman and Hadas Kress-Gazit and Marta Kwiatkowska},
booktitle = {RA-L 2018},
year = {2018}
}