Towards an Iterative Algorithm for the Optimal Boundary Coverage of a 3D Environment

This paper presents a new optimal algorithm for locating a set of sensors in 3D able to see the boundaries of a polyhedral environment. Our approach is iterative and is based on a lower bound on the sensors' number and on a restriction of the original problem requiring each face to be observed in its entirety by at least one sensor. The lower bound allows evaluating the quality of the solution obtained at each step, and halting the algorithm if the solution is satisfactory. The algorithm asymptotically converges to the optimal solution of the unrestricted problem if the faces are subdivided into smaller part

Camera Placement Planning Avoiding Occlusion: Test Results Using a Robotic Hand/Eye System

Camera placement experiments are presented that demonstrate the effectiveness of a viewpoint planning algorithm that avoids occlusion of a visual target. A CCD camera mounted on a robot in a hand-eye configuration is placed at planned unobstructed viewpoints to observe a target on a real object. The validity of the method is tested by placing the camera inside the viewing region, that is constructed using the proposed new sensor placement planning algorithm and observing whether the target is truly visible. The accuracy of the boundary of the constructed viewing region is tested by placing the camera at the critical - locations of the viewing region boundary and confirming that the target is barely visible. The corresponding scenes from the candidate viewpoints are shown demonstrating that occlusions are properly avoided

Model-Based Planning of Sensor Placement and Optical Settings

We present a model-based vision system that automatically plans the placement and optical settings of vision sensors in order to meet certain generic task requirements common to most industrial machine vision applications. From the planned viewpoints, features of interest on an object will satisfy particular constraints in the image. In this work, the vision sensor is a CCD camera equipped with a programmable lens (i.e. zoom lens) and the image constraints considered are: visibility, resolution and field of view. The proposed approach uses a geometric model of the object as well as a model of the sensor. in order to reason about the task and the environment The sensor planning system then computes the regions in space as well as the optical settings that satisfy each of the constraints separately. These results are finally combined to generate acceptable viewing locations and optical settings satisfying all constraints simultaneously. Camera planning experiments are described in which a robot-arm positions the camera at a computed location and the planned optical settings are set automatically. The corresponding scenes from the candidate viewpoints are shown demonstrating that the constraints are indeed satisfied. Other constraints, such as depth of focus, as well as other vision sensors can also be considered resulting in a fully integrated sensor planning system

Computing camera viewpoints in a robot work-cell

Automatically planning a camera viewpoint for tasks such as inspection in an active robot work-cell is a difficult problem. This paper discusses new methods for computing viewpoints which meet the feature detectability constraints of focus, field-of-view, visibility, and resolution. A theoretical outline of the method is presented, followed by experimental results and a discussion of future work

The MVP sensor planning system for robotic vision tasks

The MVP (machine vision planner) model-based sensor planning system for robotic vision is presented. MVP automatically synthesizes desirable camera views of a scene based on geometric models of the environment, optical models of the vision sensors, and models of the task to be achieved. The generic task of feature detectability has been chosen since it is applicable to many robot-controlled vision systems. For such a task, features of interest in the environment are required to simultaneously be visible, inside the field of view, in focus, and magnified as required. In this paper, we present a technique that poses the vision sensor planning problem in an optimization setting and determines viewpoints that satisfy all previous requirements simultaneously and with a margin. In addition, we present experimental results of this technique when applied to a robotic vision system that consists of a camera mounted on a robot manipulator in a hand-eye configuration

Automated sensor planning for robotic vision tasks

A method is presented to determine viewpoints for a robotic vision system for which object features of interest will simultaneously by visible, inside the field-of-view, in-focus, and magnified as required. A technique that poses the problem in an optimization setting in order to determine viewpoints that satisfy all requirements simultaneously and with a margin is presented. The formulation and results of the optimization are shown, as well as experimental results in which a robot vision system is positioned and its lens is set according to this method. Camera views are taken from the computed viewpoints in order to verify that all feature detectability requirements are satisfied

Effect of Tool-Path on Morphology and Mechanical Properties of Ti-6Al-4V Fabricated by Wire and Arc Additive Manufacturing

Ti-6Al-4V components are widely used in aerospace industry. However, it’s not economic to manufacture them in traditional subtractive methods. Wire and arc additive manufacturing (WAAM) is a promising alternative technology for fabricating it efficiently and economically. Tool-path planning strategy is a very important step in WAAM process. This paper investigated the influence of the lap way between layers and layers in tool-path on the Ti-6Al-4V samples fabricated by WAAM. It has been found that the lap way between layers and layers in tool-path do influence the forming quality and especially mechanical properties of the fabricated samples. Samples have different surface quality (smooth or undulating) and defects inside or on the surface of the components. The highest and smallest ultra tensile strength of the fabricated samples are respectively 907.86 MPa, 684.82 MPa. But it has few effect on the grains of the fabricated samples, and they all have cross-sectional columnar grains