In this paper, a new method for the calibration of robotic cell components is presented and demonstrated by identification of an industrial robotic manipulator’s base and end-effector frames in a workplace. It is based on a mathematical approach using a Jacobian matrix. In addition, using the presented method, identification of other kinematic parameters of a robot is possible. The Universal Robot UR3 was later chosen to prove the working principle in both simulations and experiment, with a simple repeatable low-cost solution for such a task—image analysis to detect tag markers. The results showing the accuracy of the system are included and discussed.
There are several ubiquitous kinematic structures that are used in industrial robots, with the most prominent being a six-axis angular structure. However, researchers are experimenting with task-based mechanism synthesis that could provide higher efficiency with custom optimized manipulators. Many studies have focused on finding the most efficient optimization algorithm for task-based robot manipulators. These manipulators, however, are usually optimized from simple modular joints and links, without exploring more elaborate modules. Here, we show that link modules defined by small numbers of parameters have better performance than more complicated ones. We compare four different manipulator link types, namely basic predefined links with fixed dimensions, straight links that can be optimized for different lengths, rounded links, and links with a curvature defined by a Hermite spline. Manipulators are then built from these modules using a genetic algorithm and are optimized for three different tasks. The results demonstrate that manipulators built from simple links not only converge faster, which is expected given the fewer optimized parameters, but also converge on lower cost values.
In this paper, we investigated the effect of the incidence angle of a laser ray on the reflected laser intensity. A dataset on this dependence is presented for materials usually used in the industry, such as transparent and non-transparent plastics and aluminum alloys with different surface roughness. The measurements have been performed with a laser line triangulation sensor and a UR10e robot. The presented results are proposing where to place the sensor relative to the scanned object, thus increasing the reliability of the sensor data collection.
Researchers often deal with the synthesis of the kinematic structure of a robotic manipulator to determine the optimal manipulator for a given task. This approach can lower the cost of the manipulator and allow it to achieve poses that might be unreachable by universal manipulators in an existing constrained environment. Numerical methods are broadly used to find the optimum design but they often require an estimated initial kinematic structure as input, especially if local-optimum-search algorithms are used. This paper presents four different algorithms for such an estimation using the standard Denavit–Hartenberg convention. Two of the algorithms are able to reach a given position and the other two can reach both position and orientation using Bézier splines approximation and vector algebra. The results are demonstrated with three chosen example poses and are evaluated by measuring manipulability and the total link length of the final kinematic structures.
The objective of this study is to extend the possibilities of robot localization in a known environment by using the pre-deployed infrastructure of a smart building. The proposed method demonstrates a concept of a Shared Sensory System for the automated guided vehicles (AGVs), when already existing camera hardware of a building can be utilized for position detection of marked devices. This approach extends surveillance cameras capabilities creating a general sensory system for localization of active (automated) or passive devices in a smart building. The application is presented using both simulations and experiments for a common corridor of a building. The advantages and disadvantages are stated. We analyze the impact of the captured frame’s resolution on the processing speed while also using multiple cameras to improve the accuracy of localization. The proposed methodology in which we use the surveillance cameras in a stand-alone way or in a support role for the AGVs to be localized in the environment has a huge potential utilization in the future smart buildings and cities. The available infrastructure is used to provide additional features for the building control unit, such as awareness of the position of the robots without the need to obtain this data directly from the robots, which would lower the cost of the robots themselves. On the other hand, the information about the location of a robot may be transferred bidirectionally between robots and the building control system to improve the overall safety and reliability of the system.
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