arescuerobotpathplanningbasedonantcolony(已修改)
2024-11-09 18:10 本頁面
【正文】 A Rescue Robot Path Planning Based on Ant Colony Optimization Algorithm School of Information Science and Engineering Central South University Changsha, Hunan 410083, China Professor： 邱俊賢 教授 Student： 黃俞融 2 Outlines Abstract 1 Introduction 2 Ant colony algorithm based path planning 3 Improved ant colony algorithm 4 Simulation and Experiment 5 Conclusion 6 3 Abstract ? This paper addressed a robot path planning algorithm based on improved ant colony optimization. A target attracting function is introduced to guide the searching process which can improve the search quality of ant colony algorithm in the plex and dynamic environment. The affectivity of proposed algorithm is verified in a standard test bed, RoboCup Rescue simulation system. ? 本文討論了機(jī)器人路徑規(guī)劃基於在改進(jìn)蟻群最佳化。 一個(gè)目標(biāo)吸引函數(shù)引入指導(dǎo)搜索過程，可以在複雜和動態(tài)的環(huán)境提高了蟻群算法的搜索品質(zhì)。提出的情感算法證實(shí)在一個(gè)標(biāo)準(zhǔn)的測詴平臺，機(jī)器人救援模擬系統(tǒng)。 4 Introduction (1/3) ? Robot path planning is an important part of the robotics. Its main task is to find a shortest path without barrier or with a minimum price from the designated original node to destination node in the environment which has obstacles. Path planning is an important ability of intelligent robots, and has great significance for acplishing the robot’s task. 機(jī)器人路徑規(guī)劃是一個(gè)機(jī)器人的重要組成部分。其主要任務(wù)是找到一個(gè)沒有障礙的最短路徑或在有障礙的環(huán)境以最低代價(jià)從原來的指定節(jié)點(diǎn)到目標(biāo)節(jié)點(diǎn)。路徑規(guī)劃是智能機(jī)器人一項(xiàng)重要的能力，並有偉大的意義去為完成機(jī)器人的任務(wù)。 5 Introduction (2/3) ? At present, the main path planning methods are as follows. a grid method which divides, an artificial potential field method, Although these methods are very practical, but it is not suit for path planning in city roads. 目前，主要的路徑規(guī)劃方法如 :網(wǎng)格劃分方法、一個(gè)人工勢場法，雖然這些方法都非常實(shí)用，但並不適合城市道路的路徑規(guī)劃。 6 Introduction (3/3) ? Ant colony algorithm can be regarded as a kind of search algorithm framework of solution space parametric based probability distribution model. So that the search in new model will focus on the quality of the search space. Because the speed of convergence is too slow, we propose a new method to improve it in this paper. 蟻群算法可以被看作是一種搜索算法的框架參數(shù)解空間概率分佈模型。因此，在新的搜索模式將側(cè)重於品質(zhì)的搜索空間。由於收斂速度太慢，本文我們提出一種新方法
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