Online Next-Best-View Planner for 3D-Exploration and Inspection With a Mobile Manipulator Robot

TL;DR

This paper introduces a novel online Next-Best-View planner for mobile manipulators that effectively balances exploration and inspection tasks, improving mapping efficiency and computational performance in outdoor environments.

Contribution

The work presents a multi-objective optimization-based NBV planner for exploration and inspection, demonstrating improved mapping and reduced computation over existing methods.

Findings

Enhanced total volume mapped in experiments

Lower computational requirements compared to baseline

Effective outdoor deployment demonstrated

Abstract

Robotic systems performing end-user oriented autonomous exploration can be deployed in different scenarios which not only require mapping but also simultaneous inspection of regions of interest for the end-user. In this work, we propose a novel Next-Best-View (NBV) planner which can perform full exploration and user-oriented exploration with inspection of the regions of interest using a mobile manipulator robot. We address the exploration-inspection problem as an instance of Multi-Objective Optimization (MOO) and propose a weighted-sum-based information gain function for computing NBVs for the RGB-D camera mounted on the arm. For both types of exploration tasks, we compare our approach with an existing state-of-the-art exploration method as the baseline and demonstrate our improvements in terms of total volume mapped and lower computational requirements. The real experiments with a mobile manipulator robot demonstrate the practicability and effectiveness of our approach outdoors.