Disassembly is a core procedure in remanufacturing. Disassembly is currently carried out mainly by human operators. It is important to reduce the labor content of dis-assembly through automation, to make remanufacturing more economically attractive. Threaded fastener removal is one of the most difficult disassembly tasks to be fully automated. This article presents a new method developed for automating the unfastening of screws. An electric nutrunner spindle with a geared offset adapter was fitted to the end of a collaborative robot. The position of a hexagonal headed screw in a fitted stage was known only approximately, and its orientation in the hole was unknown. The robot was programed to perform a spiral search motion to engage the tool onto the screw. A control strategy combining torque and position monitoring with active compliance was implemented. An existing robot cell was modified and utilized to demonstrate the concept and to assess the feasibility of the solution using a turbocharger as a disassembly case study. Note to Practitioners-Remanufacturing is known to generate substantial economic, social, and environmental benefits. Disassembly is the first operation in a remanufacturing process chain. Unfastening threaded parts ("unscrewing") is a common disassembly task accounting for approximately 40% of all disassembly activity. Like other disassembly tasks, often, unscrewing has to be carried out manually in remanufacturing due to difficulties caused by the variable and unpredictable condition of the end-of-life (EoL) products to be remanufactured. Automating unscrewing operations should reduce the labor content of disassembly, thus lowering remanufacturing costs and promoting the adoption of remanufacturing. This article proposes the use
Figure 1: Our NeRFFaceEditing method allows users to intuitively edit a facial volume to manipulate its geometry and appearance guided by rendered semantic masks. Given an input sample (a), our method disentangles its geometry and appearance, and allows for one-or multi-label editing. We show a range of flexible face editing tasks that can be achieved with our unified framework: (b) changing the appearance according to a given reference sample while retaining the geometry and 3D consistency; (c) changing the appearance for different views with different reference samples while retaining the geometry; (d) editing multiple labels of the semantic mask for a certain view while keeping the appearance and 3D consistency; (e) editing both the geometry and appearance. The inputs used to control the appearance and geometry are highlighted in green and orange boxes, respectively.
Finding a three dimensional shortest path is of importance in the development of automatic path lplanning for mobile robots and robot manipulators, and for practical implementation the algorithms require to be efficient.Presented is a method for shortest path planning in three dimensional space in the presence of convex polyhedra. It is based on the visibility graph approach, extended from two to three dimensional space. A collineatiorn is introduced for identification of visible edges in the three dimensional visibility graph. The principle of minimum potential energy is adopted for finding a set of sub-shortest paths via different edge sequences, and from them the global shortest path is selected. The three dimensional visibility graph is constructed in U(n3vk) time, where n is the number of vertices of the polyhedra, k is the number of obstacles and Y is the largest number of vertices on any one obstacle. The process to determine the shortest path runs recursively in polynomial time. Results of a computer simulation are given showing the versatility and efficiency of the approach.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.