ROMay 29, 2019

ORangE: Operational Range Estimation for Mobile Robot Exploration on a Single Discharge Cycle

arXiv:1905.12559v22 citations
Originality Incremental advance
AI Analysis

It addresses the critical issue of preventing battery depletion during autonomous missions in the wild, which is incremental as it builds on existing energy modeling approaches.

This paper tackles the problem of mobile robot exploration in unknown environments where recharging is not possible, by developing two range estimators to model energy consumption and predict operational range on a single battery discharge, with performance validated on physical robots in indoor and outdoor settings.

This paper presents an approach for estimating the operational range for mobile robot exploration on a single battery discharge. Deploying robots in the wild usually requires uninterrupted energy sources to maintain the robot's mobility throughout the entire mission. However, for most endeavors into the unknown environments, recharging is usually not an option, due to the lack of pre-installed recharging stations or other mission constraints. In these cases, the ability to model the on-board energy consumption and estimate the operational range is crucial to prevent running out of battery in the wild. To this end, this work describes our recent findings that quantitatively break down the robot's on-board energy consumption and predict the operational range to guarantee safe mission completion on a single battery discharge cycle. Two range estimators with different levels of generality and model fidelity are presented, whose performances were validated on physical robot platforms in both indoor and outdoor environments. Model performance metrics are also presented as benchmarks.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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