Resource-Performance Trade-off Analysis for Mobile Robot Design

TL;DR

This paper introduces a framework for analyzing and generating optimal resource-performance trade-offs in mobile robot design, enabling designers to select schedules that balance resource constraints with performance goals.

Contribution

It presents a multi-objective verification approach to compute Pareto fronts and automatically generate schedules tailored to resource and performance requirements.

Findings

Effective Pareto front computation for robot schedules

Automatic schedule generation meeting resource-performance trade-offs

Successful demonstrations in simulation and real experiments

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 trade off reduced resource consumption for a slightly lower but still acceptable level of performance. In this paper, we provide a framework to aid designers in exploring such resource-performance trade-offs 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 multi-objective verification technique which, for a collection of possibly conflicting objectives, produces the Pareto front that contains all the optimal trade-offs that are achievable. 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 with encouraging results.