CARE: Confidence-rich Autonomous Robot Exploration using Bayesian Kernel Inference and Optimization

TL;DR

This paper introduces a novel Bayesian kernel inference and optimization method to enhance autonomous robot exploration efficiency by accurately estimating information gain and balancing exploration and exploitation.

Contribution

It proposes a lightweight, efficient Bayesian kernel inference method (BKIO) for estimating mutual information, improving exploration efficiency without sacrificing accuracy.

Findings

BKIO achieves approximate logarithmic complexity without training.

The method maintains exploration performance in complex environments.

Extensive experiments validate the efficiency and effectiveness of the approach.

Abstract

In this paper, we consider improving the efficiency of information-based autonomous robot exploration in unknown and complex environments. We first utilize Gaussian process (GP) regression to learn a surrogate model to infer the confidence-rich mutual information (CRMI) of querying control actions, then adopt an objective function consisting of predicted CRMI values and prediction uncertainties to conduct Bayesian optimization (BO), i.e., GP-based BO (GPBO). The trade-off between the best action with the highest CRMI value (exploitation) and the action with high prediction variance (exploration) can be realized. To further improve the efficiency of GPBO, we propose a novel lightweight information gain inference method based on Bayesian kernel inference and optimization (BKIO), achieving an approximate logarithmic complexity without the need for training. BKIO can also infer the CRMI and generate the best action using BO with bounded cumulative regret, which ensures its comparable accuracy to GPBO with much higher efficiency. Extensive numerical and real-world experiments show the desired efficiency of our proposed methods without losing exploration performance in different unstructured, cluttered environments. We also provide our open-source implementation code at https://github.com/Shepherd-Gregory/BKIO-Exploration.