A. C. Sanderson, L. S. Homem de Mello, and H. Zhang. Assembly sequence planning. AI Magazine, 11(1):62-81, 1990.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....once. The predicate priority of plan 2 prioritizes the solution that uses the largest number of robots in its plan. The computation rule is determined by the definitions of prop priority 2 . 8. 2 Multiple robot assembly problem The flashlight planning problem is an example of an assembly problem [Sanderson et al. 90, Missiaen 91a] The flashlight assembly has four parts: cap, stick, receptacle, and handle. The two ends of the receptacle are designated as top(receptacle) and bottom(receptacle) The cap must be screwed onto the top of the receptacle, the handle must be screwed onto the bottom of the ....

Arthur C. Sanderson, Luiz S. Homem de Mello, and Hui Zhang. Assembly sequence planning. AI Magazine, 11(1):62-- 81, 1990.

....sequences of insertion operations. 2.3 System Inputs Ultimately, an assembly planner should be able to generate plans directly from a CAD model of the goal assembly. Several systems already support such interfaces, including those described by Hoffman[11, 12] and by Homem de Mello and Sanderson[23]. Both of these systems query the geometric models directly during the planning process. XAP 1, like De Fazio and Whitney s system, does its planning based entirely on a symbolic description of the problem. All the information that makes up this description is to be computed before the actual ....

A. C. Sanderson, L. S. Homem de Mello, and H. Zhang, "Assembly sequence planning," AI Magazine, vol. 11, no. 1, pp. 62--81, Spring 1990.

....generated by existing assembly planning systems also differ in the type and amount of detail included in the plans. The simplest type of assembly plan that has been used is the partial assembly tree shown in figure 5a. This is the type of plan generated by Homem de Mello and Sanderson s system[5, 6, 13]. Each leaf of the partial assembly tree corresponds to an individual part and each internal node corresponds to an operation that combines the two sets of parts designated by its two children. We call the assembled sets of parts resulting from each operation partial assemblies. The operations in ....

Arthur C. Sanderson, Luiz S. Homem de Mello, and Hui Zhang. Assembly sequence planning. AI Magazine, 11(1):62--81, Spring 1990.

....10 ) R 11 R 12 ) relationships target attachments nil (R 5 ) nil nil (R 13 ) relationships agent attachments nil (R 6 ) nil nil (R 14 ) relationships Table 2.1: Mello s attribute functions for the contact entities in Figure 2. 2 Homem de Mello and colleagues in their Pleiades system, described in [11], use CATIA (an IBM solid modelling and mechanical CAD design system) to design the parts model, i.e. to generate a computer representation of the geometric information of the parts in the assembly. Then they utilise Geos (a variational geometric modelling system developed at Rensselaer ....

....= 1 to l: Q1) What liaisons must be done prior to doing liaison i Q2) What liaisons must be left to be done after doing liaison i The reduction in the number of questions is, however, accompanied by a very significant increase in the difficulty of answering the questions. Mello and Sanderson [9, 11] developed a method also based on the graph of connections, but using a significantly different approach. They transformed the problem of generating assembly sequences into the problem of generating disassembly sequences in which disassembly operations are the inverse of feasible assembly ....

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A. Sanderson, L. Homem de Mello, and H. Zhang, "Assembly sequence planning, " AI Magazine, pp. 62--81, Spring 1990.

....deal with the low level planning decisions, such as selecting appropriate tools, or planning detailed tool and part movements. To create a completely automated assembly planning system both capabilities are necessary. A lot of work has been done in developing macro planners for assembly planning [6, 7, 3, 2, 12, 17, 24, 15, 20], but the area of micro planning is relatively under explored. Therefore, we have chosen to focus on micro planning. We hope that our work can later be integrated with macro planners to create a complete assembly planning system. In the mean time, we intend to rely on designers process engineers ....

A Sanderson, L Homem de Mello, and H Zhang. Assembly sequence planning. AI Magazine, 11(1):62--81, Spring 1990.

....two partial assemblies. Each node represents a partial assembly, with the root representing the complete assembly and the leaves representing the single parts. The AND OR graph data structure introduced by Homem de Mello and Sanderson is essentially the union of a set of partial assembly trees[2, 3]. A state sequence, such as those shown in figure 2, is a linear sequence of assembly states. An assembly state is represented by a partition of the part set into partial assemblies. For example, if parts A and B have been joined, but C and D remain separate, then the state would be ffA; Bg; fCg; ....

A. C. Sanderson, L. S. Homem de Mello, and H. Zhang, "Assembly sequence planning," AI Magazine, vol. 11, no. 1, pp. 62--81, Spring 1990.

....and than do a combinatorial analysis of the two types that are used in enumerative structures. 3.1 Definitions The simplest type of assembly plan that has been used in the literature is the partial assembly tree. This is the type of plan generated by Homem de Mello and Sanderson s system[10, 11, 12]. These plans can be depicted as a binary tree, such as the one shown in figure 5a. The nodes represent the partial assemblies which occur during the execution of the plan, with the singleton parts we start with at the leaves and the complete assembly at the root. The basic operation then, is to ....

A. C. Sanderson, L. S. Homem de Mello, and H. Zhang, "Assembly sequence planning," AI Magazine, vol. 11, no. 1, pp. 62--81, Spring 1990.

....promise of this approach. 2 Background Clearly any valid assembly plan must ensure that no intersections occur between the parts as they are being assembled. Some early systems accomplished this by sweeping parts along their insertion trajectories and checking for intersections with other parts[8, 19]. However this method proves computationally expensive without careful buffering and reuse of geometric query results[7] Capturing geometric information in symbolic constraint languages has led to faster planners. Two forms of constraints have been used. Insertion constraint languages consist of ....

....the first operation is specified. This can be viewed, somewhat inaccurately, as generating a disassembly sequence by repeatedly separating the assembly into two subsets, and then reversing the procedure it to achieve an assembly sequence. The planners described by Homem de Mello and Sanderson[9, 10, 19], by Lee[14] and by Wilson[21] are typical of this type approach. If the only concern is the geometric feasibility of the assembly (i.e. that parts don t intersect) then this approach has the important advantage that the planner never has to backtrack. This makes very fast non optimizing ....

Arthur C. Sanderson, Luiz S. Homem de Mello, and Hui Zhang. Assembly sequence planning. AI Magazine, 11(1):62--81, Spring 1990.

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A. C. Sanderson, L. S. Homem de Mello, and H. Zhang. Assembly sequence planning. AI Magazine, 11(1):62-81, 1990.

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Sand90 Sanderson, A.C., de MeI llo, L.S.H., and Zhang, H. Assembly Sequence Planning. AI Magazine 11, 1, Spring,1990, pp. 62-81.

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