Recently, soft grippers have garnered considerable interest in various fields, such as medical rehabilitation, due to their high compliance. However, the traditional PneuNet only reliably grasps medium and largeobjects...Recently, soft grippers have garnered considerable interest in various fields, such as medical rehabilitation, due to their high compliance. However, the traditional PneuNet only reliably grasps medium and largeobjects via enveloping grasping (EG), and cannot realize pinching grasping (PG) to stably grasp small and thinobjects as EG requires a large bending angle whereas PG requires a much smaller one. Therefore, we proposeda multi-structure soft gripper (MSSG) with only one vent per finger which combines the PneuNet in the proximal segment with the normal soft pneumatic actuator (NSPA) in the distal segment, allowing PG to be realizedwithout a loss in EG and enhancing the robustness of PG due to the height difference between the distal andproximal segments. Grasping was characterized on the basis of the stability (finger bending angle describes) androbustness (pull-out force describes), and the bending angle and pull-out force of MSSG were analyzed using thefinite element method. Furthermore, the grasping performance was validated using experiments, and the resultsdemonstrated that the MSSG with one vent per finger was able to realize PG without a loss in EG and effectivelyenhance the PG robustness.展开更多
This paper puts forward an effective, specific algorithm for edge detection. Based on multi-structure elements of gray mathematics morphology, in the light of difference between noise and edge shape of RS images, the ...This paper puts forward an effective, specific algorithm for edge detection. Based on multi-structure elements of gray mathematics morphology, in the light of difference between noise and edge shape of RS images, the paper establishes multi-structure elements to detect edge by utilizing the grey form transformation principle. Compared with some classical edge detection operators, such as Sobel Edge Detection Operator, LOG Edge Detection Operator, and Canny Edge Detection Operator, the experiment indicates that this new algorithm possesses very good edge detection ability, which can detect edges more effectively, but its noise-resisting ability is relatively low. Because of the bigger noise & remote sensing image, the authors probe into putting forward other edge detection method based on combination of wavelet directivity checkout technology and small-scale Mathematical Morphology finally. So, position at the edge can be accurately located, the noise can be inhibited to a certain extent and the effect of edge detection is obvious.展开更多
基金the National Key Research and Development Program of China(No.2020YFB1313100)。
文摘Recently, soft grippers have garnered considerable interest in various fields, such as medical rehabilitation, due to their high compliance. However, the traditional PneuNet only reliably grasps medium and largeobjects via enveloping grasping (EG), and cannot realize pinching grasping (PG) to stably grasp small and thinobjects as EG requires a large bending angle whereas PG requires a much smaller one. Therefore, we proposeda multi-structure soft gripper (MSSG) with only one vent per finger which combines the PneuNet in the proximal segment with the normal soft pneumatic actuator (NSPA) in the distal segment, allowing PG to be realizedwithout a loss in EG and enhancing the robustness of PG due to the height difference between the distal andproximal segments. Grasping was characterized on the basis of the stability (finger bending angle describes) androbustness (pull-out force describes), and the bending angle and pull-out force of MSSG were analyzed using thefinite element method. Furthermore, the grasping performance was validated using experiments, and the resultsdemonstrated that the MSSG with one vent per finger was able to realize PG without a loss in EG and effectivelyenhance the PG robustness.
基金Foundation item: Under the auspices of the National Natural Science Foundation of China (No. 49971055
文摘This paper puts forward an effective, specific algorithm for edge detection. Based on multi-structure elements of gray mathematics morphology, in the light of difference between noise and edge shape of RS images, the paper establishes multi-structure elements to detect edge by utilizing the grey form transformation principle. Compared with some classical edge detection operators, such as Sobel Edge Detection Operator, LOG Edge Detection Operator, and Canny Edge Detection Operator, the experiment indicates that this new algorithm possesses very good edge detection ability, which can detect edges more effectively, but its noise-resisting ability is relatively low. Because of the bigger noise & remote sensing image, the authors probe into putting forward other edge detection method based on combination of wavelet directivity checkout technology and small-scale Mathematical Morphology finally. So, position at the edge can be accurately located, the noise can be inhibited to a certain extent and the effect of edge detection is obvious.
