In this letter, a simple and compact directivity enhancement of slot antenna using a grounded metamaterial slab is proposed. This approach two different configurations. In the first configuration dielectric layers are used for designing antenna and metamaterial slab. Despite the directivity enhancement bandwidth of about 10.74% is obtained for It is also shown that, over the whole working band broadside directivity improvement is maintained the unloaded slot. In the second configuration of dielectric is used for designing both antenna and metamaterial slab. Thus, in this case, the total thickness of the loaded is noticeably reduced to 0.5 mm, or 0 0.014 λ a simple and compact approach for directivity enhancement of slot antenna using a grounded This approach has been applied in In the first configuration, two for designing antenna and metamaterial directivity enhancement, an improved for this configuration. , over the whole working band, a significant maintained compared to configuration, only a single layer of dielectric is used for designing both antenna and metamaterial of the loaded antenna 0 λ at resonance.Waveguide (CPW), Slot, MNZ and EVL Metamaterial, Leaky wave, Directivity enhancement.
This paper looks into the problem of grasping unknown objects in a cluttered environment using 3D point cloud data obtained from a range or an RGBD sensor. The objective is to identify graspable regions and detect suitable grasp poses from a single view, possibly, partial 3D point cloud without any apriori knowledge of the object geometry. The problem is solved in two steps: (1) identifying and segmenting various object surfaces and, (2) searching for suitable grasping handles on these surfaces by applying geometric constraints of the physical gripper. The first step is solved by using a modified version of region growing algorithm that uses a pair of thresholds for smoothness constraint on local surface normals to find natural boundaries of object surfaces. In this process, a novel concept of edge point is introduced that allows us to segment between different surfaces of the same object. The second step is solved by converting a 6D pose detection problem into a 1D linear search problem by projecting 3D cloud points onto the principal axes of the object surface. The graspable handles are then localized by applying physical constraints of the gripper. The resulting method allows us to grasp all kinds of objects including rectangular or box-type objects with flat surfaces which have been difficult so far to deal with in the grasping literature. The proposed method is simple and can be implemented in real-time and does not require any off-line training phase for finding these affordances. The improvements achieved is demonstrated through comparison with another state-of-the-art grasping algorithm on various publicly-available and self-created datasets.
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