A framework for multi-robot coverage analysis of large and complex structures

Abstract

Coverage analysis is essential for many coverage tasks (e.g., robotic grit-blasting, painting and surface cleaning) performed by Autonomous Industrial Robots (AIRs). Coverage analysis enables (1) the performance evaluation (e.g., coverage rate and operation efficiency) of AIRs for a coverage task, and (2) the configuration design of a multi-AIR system (e.g., decision on the number of AIRs to be used). Multi-AIR coverage analysis of large and complex structures involves addressing various problems. Thus, a framework is presented in this paper that incorporates various modules (e.g., AIR reachability, AIR base placement, collision avoidance, and area partitioning and allocation) for appropriately addressing the associated problems. The modules within the framework provide the flexibility of utilizing different methods and algorithms, depending on the requirements of the target application. The framework is tested and validated by extensive analyses of 10 different scenarios with up-to 10 AIRs.

Robotic Coverage Path Planning for Ultrasonic Inspection

“…In addition, the method adaptively selects the next region to be measured in each step. An interesting extension of coverage path planning deals with multi-robot environments [13,14]. For most applications, this requires some kind of synchronization of robots.…”

Task allocation and coordinated motion planning for autonomous multi-robot optical inspection systems

“…Åblad et al (2017) developed a surrogate model-based approach to partition the entire workspace and separate the workspace of each robot from the workspace of other robots to avoid conflicts. Dai et al (2021) developed a framework to analyze the multi-robot coverage of large complex structures. Liu et al (2014) proposed the dynamic priority-based path planning to address collision avoidance for the cooperation of multiple mobile robots.…”