關(guān)于機(jī)械手的中英文翻譯--機(jī)器人控制和裝配計(jì)劃相結(jié)合的精密機(jī)械手

1、徐州工程學(xué)院畢業(yè)設(shè)計(jì)外文翻譯學(xué) 生 姓 名學(xué) 院 名 稱專 業(yè) 名 稱指 導(dǎo) 教 師20**年 5 月 27 日A skill-based micromanipulation system has been developed in the authors’ lab, and it can realize many micromanipulation operations. In the system, the assembly tas

2、k is manually discomposed into skill sequences and compiled into a file. After importing the file into the system, the system can automatically execute the assembly task. This paper attempts to explore a user-friendly, a

3、nd at the same time easy, sequence-generation method, to relieve the burden of manually programming the skillsequence.It is an effective method to determine the assembly sequence from geometric computer-aided design (CAD

4、) models. Many approaches have been proposed. This paper applies a simple approach to generate the assembly sequence. It is not involved with the low-level data structure of the CAD model, and can be realized with the ap

5、plication programming interface (API) functions that many commercial CAD software packages provide. In the proposed approach, a relations graph among different components is first constructed by analyzing the assembly mo

6、del, and then, possible sequences are searched, based onthe graph. According to certain criterion, the optimal sequence is finally obtained. To decompose the assembly sequence into robot skill sequences, some works have

7、been reported. In Nnaji et al.’s work, the assembly task commands are expanded to more detailed commands, which can be seen as robot skills, according to a predefined format. The decomposition approach of Mosemann and Wa

8、hl is based on the analysis of hyperarcs of AND/OR graphs representing the automatically generated assembly plans. This paper proposes a method to guide the skill decomposition. The assembly processes of parts are groupe

9、d into different phases, and parts are at different states. Specific workflows push forward parts from one state to another state. Each workflow is associated with a skill generator. According to the different start stat

10、e and target state of the workflow, the skill generator creates a series of skills that can promote the part to its target state.The hierarchy of the system proposed here ,the assembly information on how to assemble a pr

11、oduct is transferred to the robot through multiple layers. The top layer is for the assembly-task planning. The information needed for the task planning and skill generation are extracted from the CAD model and are saved

12、 in the database. Based on the CAD model, the assembly task sequences are generated. At the skill-decomposition layer, tasks are decomposed into skill sequences. The generated skills are managed and executed at the robot