Rethinking Energy Management for Autonomous Ground Robots on a Budget

TL;DR

This paper introduces PECC, a framework that optimizes computing and locomotion to improve autonomous ground robot performance within energy limits, outperforming energy-efficient baselines in real and simulated tests.

Contribution

The paper presents PECC, a novel integrated approach to optimize energy consumption and performance in AGRs by jointly adjusting computing frequency and locomotion speed.

Findings

AGR travels 17% faster than baseline in real tests

AGR travels 31% faster than baseline in simulations

PECC consumes over 90% of the energy budget while improving performance

Abstract

Autonomous Ground Robots (AGRs) face significant challenges due to limited energy reserve, which restricts their overall performance and availability. Prior research has focused separately on energy-efficient approaches and fleet management strategies for task allocation to extend operational time. A fleet-level scheduler, however, assumes a specific energy consumption during task allocation, requiring the AGR to fully utilize the energy for maximum performance, which contrasts with energy-efficient practices. This paper addresses this gap by investigating the combined impact of computing frequency and locomotion speed on energy consumption and performance. We analyze these variables through experiments on our prototype AGR, laying the foundation for an integrated approach that optimizes cyber-physical resources within the constraints of a specified energy budget. To tackle this challenge, we introduce PECC (Predictable Energy Consumption Controller), a framework designed to optimize computing frequency and locomotion speed to maximize performance while ensuring the system operates within the specified energy budget. We conducted extensive experiments with PECC using a real AGR and in simulations, comparing it to an energy-efficient baseline. Our results show that the AGR travels up to 17\% faster than the baseline in real-world tests and up to 31\% faster in simulations, while consuming 95\% and 91\% of the given energy budget, respectively. These results prove that PECC can effectively enhance AGR performance in scenarios where prioritizing the energy budget outweighs the need for energy efficiency.