本文選題：生物激勵(lì)神經(jīng)網(wǎng)絡(luò)　切入點(diǎn)：模糊邏輯　出處：《南昌大學(xué)》2016年碩士論文

【摘要】：隨著智能技術(shù)與社會(huì)生產(chǎn)、生活的不斷結(jié)合,全球制造業(yè)正在向數(shù)字化、智能化、綠色化、自動(dòng)化方向發(fā)展。作為智能制造的主力軍,機(jī)器人由于具備了高智能性、高效工作效率和精確性、能夠代替人類完成重復(fù)或危險(xiǎn)的任務(wù)等優(yōu)點(diǎn),在生產(chǎn)生活方面得到普及。人們對(duì)機(jī)器人的靈活性及智能也提出更高的要求,其中路徑規(guī)劃問題就是一項(xiàng)重要的研究課題,而全覆蓋路徑規(guī)劃又是其中一種較特殊又有著廣泛應(yīng)用前景的形式。本文在對(duì)生物激勵(lì)神經(jīng)網(wǎng)絡(luò)算法進(jìn)行詳細(xì)分析的基礎(chǔ)上,對(duì)其存在的問題進(jìn)行改進(jìn),并且提出將模糊邏輯算法用于障礙物邊界探測中,實(shí)時(shí)更新環(huán)境地圖,最后通過仿真驗(yàn)證。本課題主要完成下面的幾點(diǎn)工作:1.對(duì)目前常用的地圖構(gòu)建方法、行走方式和全覆蓋路徑規(guī)劃算法進(jìn)行研究分析、對(duì)比各自的缺點(diǎn),在此基礎(chǔ)之上,確定了本課題所選用的算法。針對(duì)所選算法的特點(diǎn),確定了與之相匹配的柵格環(huán)境建模法和往復(fù)式行走方式。2.在已知的工作環(huán)境中,通過生物激勵(lì)神經(jīng)網(wǎng)絡(luò)算法進(jìn)行全覆蓋路徑規(guī)劃,對(duì)該過程進(jìn)行詳細(xì)闡述。針對(duì)拐點(diǎn)處方向不確定性的問題進(jìn)行分析并提出相應(yīng)的改進(jìn)方法,并通過仿真實(shí)驗(yàn)驗(yàn)證改進(jìn)方法的有效性。3.針對(duì)未知環(huán)境中缺少全方位信息的問題,引入了模糊邏輯算法進(jìn)行障礙物邊界探測,詳細(xì)闡明了該過程。并且將基于生物激勵(lì)神經(jīng)網(wǎng)絡(luò)的全局規(guī)劃與基于模糊邏輯的局部規(guī)劃相融合,實(shí)現(xiàn)在未知環(huán)境中的全覆蓋,并通過仿真,證明該思想的可行性。
[Abstract]:With the combination of intelligent technology and social production and life, the global manufacturing industry is developing towards digitalization, intelligentization, greening and automation. As the main force of intelligent manufacturing, robot has high intelligence. The high efficiency and precision of work, which can replace the human being to complete repetitive or dangerous tasks, have been popularized in production and life. People also put forward higher demands on the flexibility and intelligence of robots. The path planning problem is an important research topic, and the full coverage path planning is one of the more special and widely applied forms. This paper analyzes the biological excitation neural network algorithm in detail. The existing problems are improved, and the fuzzy logic algorithm is used in obstacle boundary detection to update the environmental map in real time. Finally, through the simulation verification. This topic mainly completes the following several work: 1.carries on the research and analysis to the current commonly used map construction method, the walking way and the full coverage path planning algorithm, compares each shortcoming, on this basis, According to the characteristics of the selected algorithm, the corresponding grid environment modeling method and reciprocating walking mode. 2. In the known working environment, The full coverage path planning is carried out through the biological excitation neural network algorithm, and the process is described in detail. The problem of the direction uncertainty at the inflection point is analyzed and the corresponding improvement method is put forward. The effectiveness of the improved method is verified by simulation experiments. 3. Aiming at the lack of omnidirectional information in unknown environment, the fuzzy logic algorithm is introduced to detect the boundary of obstacles. The process is explained in detail, and the global planning based on biological excitation neural network is combined with the local programming based on fuzzy logic to realize full coverage in unknown environment, and the feasibility of the idea is proved by simulation.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP242

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本文編號(hào)：1679888