Computationally-Efficient Roadmap-based Inspection Planning via Incremental Lazy Search

TL;DR

This paper enhances the IRIS inspection planning algorithm by integrating lazy edge-evaluation and search reuse techniques, significantly accelerating plan computation for real-world applications without sacrificing optimality.

Contribution

It introduces computational improvements to IRIS, enabling faster inspection plan generation through lazy evaluation and local search reuse, applicable to complex real-world scenarios.

Findings

Inspection plans computed 570x faster in some scenarios

Enhanced IRIS maintains asymptotic optimality

Applicable to bridge and surgical inspection tasks

Abstract

The inspection-planning problem calls for computing motions for a robot that allow it to inspect a set of points of interest (POIs) while considering plan quality (e.g., plan length). This problem has applications across many domains where robots can help with inspection, including infrastructure maintenance, construction, and surgery. Incremental Random Inspection-roadmap Search (IRIS) is an asymptotically-optimal inspection planner that was shown to compute higher-quality inspection plans orders of magnitudes faster than the prior state-of-the-art method. In this paper, we significantly accelerate the performance of IRIS to broaden its applicability to more challenging real-world applications. A key computational challenge that IRIS faces is effectively searching roadmaps for inspection plans -- a procedure that dominates its running time. In this work, we show how to incorporate lazy edge-evaluation techniques into \iris's search algorithm and how to reuse search efforts when a roadmap undergoes local changes. These enhancements, which do not compromise IRIS's asymptotic optimality, enable us to compute inspection plans much faster than the original IRIS. We apply IRIS with the enhancements to simulated bridge inspection and surgical inspection tasks and show that our new algorithm for some scenarios can compute similar-quality inspection plans 570x faster than prior work.