Computer-Aided Inspection Planning (CAIP) has been a research topic for the past 25 years. Most of the CAIP systems were developed for Coordinate Measuring Machines (CMMs). The authors reviewed these CAIP systems and categorized them into two groups: tolerance-driven and geometry-based CAIP systems. Compared with CMMs, On-Machine Inspection (OMI) systems provide direct inspection in manufacturi...

The aim of this work is fast, automated planning of robotic inspections involving complex 3D structures. A model comprised of discrete geometric primitives is provided as input, and a feasible robot inspection path is produced as output. Our algorithm is intended for tasks in which 2.5D algorithms, which divide an inspection into multiple 2D slices, and segmentation-based approaches, which divi...

The significant computational efforts required to compute risk-based inspection plans founded on the Bayesian decision theory has hindered their application in the past. In this article, a computationally efficient method for the calculation of risk-based inspection (RBI) plans is presented, which overcomes the problem through the use of a generic approach. After an introduction in RBI planning...

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The autonomous inspection of complex environments is a challenging task. An autonomous inspection robot should actively examine entities of interest (EOIs), e.g. defects, and should perform additional inspection actions until the data analysis results reach an appropriate level of confidence. In this paper a semantic approach for inspection planning, plan execution, assessment of the data analy...

This paper addresses the following inspection problem: given a known workspace and a robot with vision capabilities compute a short path path for the robot such that each point on boundary of the workspace is visible from some point on the path. Autonomous inspection, such as by a flying camera, or a virtual reality architectural walkthrough, could be guided by a solution to the above inspectio...

1 Currently on sabbatical leave at the Fraunhofer Institute for Experimental Software Engineering, Sauerwiesen 6, D-67661 Kaiserslautern, Germany. This work has been funded in part under the Austrian Science Fund grant J-1948-INF.

Models of planning under uncertainty, and in particular, MDPs and POMDPs have received much attention in the AI and DecisionTheoretic planning communities (Boutilier, Dean, and Hanks 1999; Kaelbling, Littman, and Cassandra 1998). These models allow for a richer and more realistic representation of real-world planning problems, but lead to increased complexity. Recently, a new approach for handl...