Resource-Performance Tradeoff Analysis for Mobile Robots

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.