Viewpoint placement for inspection planning

Abstract

Inspection planning approaches so far have focused on automatically obtaining an optimal set of viewpoints required to cover a given object. While research has provided interesting results, the automatic inspection planning has still not been made a part of the everyday inspection system development process. This is mostly because the plans are difficult to verify and it is impossible to compare them to laboratory-developed plans. In this work, we give an overview of available generate-and-test approaches, evaluate their results for various objects and finally compare them to plans created by inspection system development experts. The comparison emphasizes both benefits and downsides of automated approaches and highlights problems which need to be tackled in the future in order to make the automated inspection planning more applicable.

Viewpoint Generation Using Feature-Based Constrained Spaces for Robot Vision Systems

“…Within his work, Scott considered further sensor parameters, e.g., the shadow effect, measurement precision, and the incident angle, which many others have neglected. More recent works [3,[22][23][24] confirmed the benefits of such an approach and used the concept of visibility matrices for encoding information between a surface point and a set of valid viewpoints.…”

“…To answer this question, this study proposes the characterization of Feature-Based Constrained Spaces (C-spaces). The C-space denoted as C can be regarded as the geometrical representation of all viewpoint constraints in the special Euclidean group SE (3). Any sensor pose within it ∀ p s ∈C can be considered to be valid to acquire a feature satisfying all viewpoint constraints C. The C-space is constituted by individual C-spaces C i (c i ), i.e., geometrical representations of each viewpoint constraint c i ∈ C.…”

“…Continuous vs. Discrete Space: Most of the latest research has followed a synthesis approach based on visibility matrices or visibility maps to encode the surface space and viewpoint space together for a handful of applications and systems [3,[22][23][24]30]. Although these works have demonstrated the use of discrete spaces to be practical and efficient, from our point of view, its major weakness lies in the intrinsic limited storage capacity and processing times associated with matrices.…”

“…In our work, we assume that the robot workspace is known and can be characterized by a manifold in the special Euclidean group SE (3). Considering this assumption, the constrained space C 8 can be seamlessly intersected with the rest of the viewpoint constraints.…”

“…Whether programmed offline or online, RVSs demand multiple planning modules to execute motion and vision tasks efficiently and robustly. For instance, the efficient and effective planning of valid viewpoints to fulfill a vision task considering different constraints, known as the view(point) planning problem (VPP), still represents an open planning problem within diverse applications [2,3], e.g., camera surveillance, scene exploration, object detection, visual servoing, object reconstruction, image-based inspection, robot calibration, and mobile navigation [2,4].…”