【摘要】：為了使機(jī)器人在復(fù)雜動(dòng)態(tài)環(huán)境中實(shí)現(xiàn)最優(yōu)路徑規(guī)劃,提出了改進(jìn)人工蜂群算法的路徑規(guī)劃方法。分析了傳統(tǒng)的人工蜂群算法原理,引入了小步長(zhǎng)偵查蜂為跟隨蜂提供障礙物分布的先驗(yàn)信息;為了防止機(jī)器人與動(dòng)態(tài)障礙物發(fā)生碰撞,對(duì)動(dòng)態(tài)障礙物周圍的可行節(jié)點(diǎn)進(jìn)行障礙化處理,將節(jié)點(diǎn)障礙指數(shù)與節(jié)點(diǎn)與目標(biāo)點(diǎn)距離糅合為節(jié)點(diǎn)選擇準(zhǔn)則,同時(shí)提出了障礙避撞預(yù)測(cè)和障礙避撞策略。由仿真實(shí)驗(yàn)可以看出,改進(jìn)算法不僅成功實(shí)現(xiàn)避撞,而且規(guī)劃出避撞條件下的最優(yōu)路徑。
[Abstract]:In order to realize optimal path planning of robot in complex dynamic environment, a path planning method based on improved artificial colony algorithm is proposed. The principle of traditional artificial bee colony algorithm is analyzed, and a small step-size detection bee is introduced to provide prior information of obstacle distribution for follow-up bee. In order to prevent the robot from colliding with the dynamic obstacle, the feasible nodes around the dynamic obstacle are treated with obstacles, and the node obstacle index and the distance between the node and the target point are combined as the node selection criteria. At the same time, the prediction of obstacle avoidance and the strategy of obstacle avoidance are put forward. It can be seen from the simulation experiment that the improved algorithm not only successfully realizes collision avoidance, but also plans the optimal path under the condition of collision avoidance.
【作者單位】： 上海第二工業(yè)大學(xué);
【基金】：國(guó)家自然科學(xué)基金(61272470) 上海第二工業(yè)大學(xué)校級(jí)重點(diǎn)學(xué)科建設(shè)資助(NO:XXKPY1603)
【分類號(hào)】：TP242

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