The automated handling of workpieces is one of the main enablers for automatic production systems and requires a stable grasping point determination. To select suitable grasp candidates for STL based models with a planar parallel jaw gripper we propose a two stage algorithm. First, the STL file is remeshed to create a boundary layer containing triangles for every surface of the handling object through a shifting of its edges. In the second step, antipodal grasping positions are determined with the use of local convex hulls, which are generated via a Delaunay3D triangulation, and through an orientation examination to classify the area as convex or concave. Based on this classification all convex points are cross checked to identify pairs of antipodal Points and the associated grasping position. An evaluation of our approach was performed on a test set containing 10 different industrial and everyday objects ranging from gears and shafts to sockets and a freeform body. For all objects a highly diverse solution set could be generated and through the remeshing process the number of grasping positions could be enlarged by at least 38 % for all objects.
To generate suitable grasping positions between tessellated handling objects and specific planar grippers, we propose a 2D analytical approach which uses a polygon clipping algorithm to generate detailed information about the intersection between both objects. With the generated knowledge about the intersection we check whether its shape fits to the set criteria of the operator and represents a valid grasping position. Before the polygon clipping algorithm is applied, a preprocessing step is performed, where appropriate surfaces from the handling object and the gripper are extracted. After rotating all surfaces into a common plane, potential clipping positions are detected and the clipping is performed to get an accurate intersection detection. The validation shows comparable running times to a OBBTree algorithm (0.1 ms per grasping position) while increasing the stability of the results from 30 to 100% for the evaluated test objects.
A general pattern recognition (i.e. data acquisition + feature extraction + classification) system for automatic analyses of electrocardiographic body surface potential maps (BSPM) is presented. After data acquisition and preprocessing of the cardiac potentials a small number of descriptive features with high discriminatory power is extracted from the spatial BSPM patterns of the potential field. In the following an automatic classification of the features into several diagnostic groups of abnormality allows the assessment of the BSPM data. The structure of the developed research system is presented and the ideas of some of the implemented algorithms of feature extraction are elucidated and compared. As examples of application body surface potential mapping data are evaluated (A) from 90 patients with acute myocardial infarction (AMI) to determine the location of the coronary occlusion, ( 6 ) from 51 patients with old myocardial infarction (OMI) and a control group to assess, if the patient had had an infarction or not, and (C) from 21 patients after orthotopic heart transplantation (HTX) to determine the grade of rejection of the transplanted heart. In all three studies only a few features (2 to 6) were sufficient to achieve a clear conformity to the invasive diagnosis (AMI, OM/: angiography; HTX: endomyocardial biopsie) and to classify the BSPM patterns correctly (best recognition rate AMI: 96 percent; OM'; 100 percent; HTX: 75 percent).
In the context of Industry 4.0 and cyber-physical production systems, the role of production logistics is perceived as more and more important in order to reach the overall manufacturing targets. One central aspect in organizing the flow of material consists in task allocation and path planning for transport resources disposing of growing autonomy. There are various approaches for multi-agent path planning as well as the way of dealing with collisions. Collisions are possible due to traffic volume and can either be treated on planning level or in a short-term way on control level. The paper presents existing strategies for path finding before giving an overview of methods to deal with autonomous transport resources that meet in a manufacturing environment. Then, different existing behaviors and reactions in the case of collision detection based on several criteria are compared. This step allows classifying the strategies depending on the manufacturing environment and its organization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.