多移動機(jī)器人協(xié)調(diào)規(guī)劃算法研究
發(fā)布時間：2018-08-12 10:58
【摘要】：通過協(xié)調(diào)控制,多個移動機(jī)器人可以實(shí)現(xiàn)單個移動機(jī)器人無法或難以完成的任務(wù)：搜索危險環(huán)境、運(yùn)輸救援物資、或圍捕目標(biāo)等。為了完成上述任務(wù),多移動機(jī)器人的路徑規(guī)劃、編隊規(guī)劃、區(qū)域覆蓋空洞檢測與修復(fù)、以及區(qū)域中發(fā)生事件的檢測及覆蓋都是需要解決的關(guān)鍵問題。本論文主要針對多移動機(jī)器人協(xié)調(diào)控制中上述幾方面關(guān)鍵問題展開研究,提出一系列解決上述問題的算法,研究內(nèi)容主要包括以下四個方面。(1)提出了適用于多移動機(jī)器人路徑規(guī)劃的多克隆人工免疫網(wǎng)絡(luò)算法在復(fù)雜、動態(tài)變化的未知環(huán)境中,根據(jù)移動機(jī)器人攜帶傳感器獲得的環(huán)境信息及機(jī)器人自身狀態(tài)信息,快速、有效地規(guī)劃一條安全無碰撞路徑,是多移動機(jī)器人順利完成任務(wù)的前提。動態(tài)環(huán)境中,移動障礙和移動目標(biāo)的運(yùn)動方程難以獲得,未知環(huán)境的數(shù)學(xué)模型難以建立,如何根據(jù)障礙和目標(biāo)的實(shí)時位置規(guī)劃安全路徑是研究的一個難點(diǎn)。針對存在多個靜止障礙的未知環(huán)境中的單移動機(jī)器人路徑規(guī)劃問題,提出一種多克隆人工免疫網(wǎng)絡(luò)算法。該算法將傳感器獲得的環(huán)境信息定義為抗原,將機(jī)器人可能的運(yùn)動方向定義為抗體,根據(jù)生物免疫機(jī)理、抗原與抗體之間的相互作用,計算并選擇出最優(yōu)運(yùn)動方向角。針對免疫解空間中的未成熟收斂問題,采用多克隆操作,通過增加抗體多樣性解決。另外,該算法也解決了人工勢場法存在的局部極小問題。多克隆人工免疫網(wǎng)絡(luò)算法可以成功避開環(huán)境中存在的多個靜止障礙,以最優(yōu)路徑成功到達(dá)目標(biāo)位置。仿真結(jié)果及分析說明了算法的有效性,與其余算法的比較說明了算法的優(yōu)越性。針對存在多個移動障礙、移動目標(biāo)的未知環(huán)境中的多移動機(jī)器人動態(tài)路徑規(guī)劃問題,提出一種改進(jìn)多克隆人工免疫網(wǎng)絡(luò)算法。該算法在多克隆人工免疫網(wǎng)絡(luò)算法的基礎(chǔ)上,考慮了其余機(jī)器人、移動障礙及移動目標(biāo)的影響,重新定義了抗原、抗體相互作用模型。另外,引入記憶單元,將機(jī)器人遇到過的環(huán)境信息、及針對該環(huán)境做出特異性響應(yīng)的抗體存儲。該算法可以根據(jù)移動障礙及移動目標(biāo)的實(shí)時位置,重新選擇出最優(yōu)運(yùn)動方向角。記憶能力不僅能夠增加特異性反應(yīng)被選擇的概率,而且可以減少動態(tài)路徑規(guī)劃的響應(yīng)時間。仿真結(jié)果及分析說明了算法的有效性,與其余算法的比較說明了算法的優(yōu)越性。(2)提出了適用于多移動機(jī)器人編隊規(guī)劃的多克隆人工免疫網(wǎng)絡(luò)算法實(shí)際應(yīng)用中,為了充分獲取環(huán)境信息、增強(qiáng)抵御外界入侵的能力、提高任務(wù)完成效率,需要對多個移動機(jī)器人進(jìn)行編隊。在復(fù)雜環(huán)境中,根據(jù)多移動機(jī)器人所配置傳感器獲得的環(huán)境信息及機(jī)器人自身狀態(tài)信息,如何形成合適隊形并維持、切換不同隊形,同時有效避障,是多移動機(jī)器人編隊研究的重點(diǎn)問題。針對存在多個障礙的未知環(huán)境中多移動機(jī)器人動態(tài)編隊問題,采用改進(jìn)多克隆人工免疫網(wǎng)絡(luò)算法解決。根據(jù)領(lǐng)航機(jī)器人、跟隨機(jī)器人間的期望距離和期望角度計算得到期望隊形,改進(jìn)多克隆人工免疫網(wǎng)絡(luò)算法保證多移動機(jī)器人系統(tǒng)形成、并維持期望隊形運(yùn)動,同時避開障礙。圖論理論的引入,實(shí)現(xiàn)了兩種同構(gòu)隊形之間的平滑切換,并用于機(jī)器人避障。環(huán)境變化時,機(jī)器人角色及期望隊形可以隨之改變,實(shí)現(xiàn)動態(tài)編隊。仿真結(jié)果及分析說明了算法的有效性。針對跟隨機(jī)器人避障以及隊形形成、隊形維持問題,從不同角度、采用不同力法計算跟隨機(jī)器人的運(yùn)動方向角與線速度。跟隨機(jī)器人的運(yùn)動方向角采用多克隆人工免疫網(wǎng)絡(luò)算法計算,不僅可以快速趨于領(lǐng)航機(jī)器人的方向角,而且可以成功避開障礙。跟隨機(jī)器人的線速度采用位置跟蹤控制法計算,可以保證跟隨機(jī)器人的位置誤差快速趨于零,形成期望隊形。另外,根據(jù)李雅普諾夫理論證明了整個編隊系統(tǒng)的漸進(jìn)穩(wěn)定性。利用仿真和MobileSim實(shí)驗(yàn)對算法進(jìn)行了驗(yàn)證、比較。(3)提出了適用于移動傳感器網(wǎng)絡(luò)覆蓋空洞檢測與修復(fù)的sub-Voronoi單元面積法移動傳感器網(wǎng)絡(luò)中的區(qū)域覆蓋具有重要的現(xiàn)實(shí)意義及廣泛的潛在實(shí)際應(yīng)用：室內(nèi)外清掃、掃雷排雷、事故現(xiàn)場搜救、農(nóng)田播種等。移動機(jī)器人可以視為傳感器網(wǎng)絡(luò)中的移動傳感器節(jié)點(diǎn),所有適用于傳感器網(wǎng)絡(luò)中移動節(jié)點(diǎn)區(qū)域覆蓋的算法均適用于移動機(jī)器人區(qū)域覆蓋。覆蓋空洞的出現(xiàn)會導(dǎo)致監(jiān)測信息感知不完整,對網(wǎng)絡(luò)的連通性造成影響,甚至導(dǎo)致網(wǎng)絡(luò)整體失效,嚴(yán)重影響傳感器網(wǎng)絡(luò)的性能和服務(wù)質(zhì)量。在有限節(jié)點(diǎn)數(shù)量的傳感器網(wǎng)絡(luò)中,如何檢測并修復(fù)覆蓋空洞,提高區(qū)域覆蓋率及節(jié)點(diǎn)覆蓋效率,改善移動傳感器網(wǎng)絡(luò)性能,是移動傳感器網(wǎng)絡(luò)區(qū)域覆蓋的研究重點(diǎn)。為了實(shí)現(xiàn)移動傳感器網(wǎng)絡(luò)區(qū)域覆蓋,針對區(qū)域中出現(xiàn)的覆蓋空洞,提出一種基于sub-Voronoi單元面積法的覆蓋空洞檢測與修復(fù)算法。該算法將每個Voronoi單元劃分為多個sub-Voronoi單元,根據(jù)sub-Voronoi單元與節(jié)點(diǎn)感知圓之間的幾何關(guān)系,計算每個sub-Voronoi單元內(nèi)覆蓋空洞的面積,進(jìn)而判斷是否存在覆蓋空洞。為了完成覆蓋空洞修復(fù),移動節(jié)點(diǎn)朝向空洞面積最大的sub-Voronoi內(nèi)的最優(yōu)位置運(yùn)動。該算法不僅可以估計出每個Voronoi單元內(nèi)覆蓋空洞的位置,而且可以準(zhǔn)確計算出每一個sub-Voronoi單元內(nèi)覆蓋空洞的面積,同時還可以快速最大化區(qū)域覆蓋率、節(jié)點(diǎn)覆蓋效率,實(shí)現(xiàn)空洞修復(fù),最大化網(wǎng)絡(luò)利用率。利用仿真對算法進(jìn)行驗(yàn)證、比較。(4)提出了適用于多移動機(jī)器人系統(tǒng)的多事件動態(tài)k-覆蓋規(guī)劃算法多移動機(jī)器人監(jiān)測區(qū)域中可能會發(fā)生各種事件,如何以最少的能量消耗完成區(qū)域覆蓋、及時檢測到事件、并對事件進(jìn)行覆蓋,是多移動機(jī)器人區(qū)域覆蓋的另一個研究重點(diǎn)。針對多移動機(jī)器人系統(tǒng)中的多事件動態(tài)k-覆蓋規(guī)劃問題展開研究,將其分為兩個子問題：移動機(jī)器人均勻分布、節(jié)點(diǎn)選擇。首先,為了有效與靜態(tài)節(jié)點(diǎn)進(jìn)行通信、盡可能覆蓋整個區(qū)域,隨機(jī)分布的稀疏移動機(jī)器人需要盡可能實(shí)現(xiàn)均勻部署。提出WSVHG、WSVHI兩種方法實(shí)現(xiàn)移動機(jī)器人均勻部署。然后,在檢測到事件時,采用類博弈論法選擇出k個要對事件進(jìn)行覆蓋的移動機(jī)器人,類博弈論法考慮了節(jié)點(diǎn)的剩余能量、運(yùn)動能量、通信能量。該算法保證機(jī)器人可以以較高的覆蓋率完成區(qū)域覆蓋,并且可以以較少的能量消耗完成多事件的k-覆蓋。仿真驗(yàn)證及算法比較分析說明了算法的有效性。
[Abstract]:Through coordinated control, multiple mobile robots can accomplish tasks that a single mobile robot cannot or cannot accomplish: searching for dangerous environments, transporting rescue materials, or enclosing and catching targets. Detection and coverage are the key problems to be solved. In this paper, a series of algorithms are proposed to solve the above-mentioned problems in the coordinated control of multi-mobile robots. The research contents mainly include the following four aspects. (1) A multi-clonal artificial robot for path planning of multi-mobile robots is proposed. Immune network algorithm can quickly and effectively plan a safe collision-free path in complex and dynamic unknown environment according to the environment information obtained by the mobile robot carrying sensors and the state information of the robot itself. It is difficult to obtain the equation and establish the mathematical model of the unknown environment. How to plan the safe path according to the real-time location of obstacles and targets is a difficult problem in the research. The obtained environmental information is defined as antigen, and the possible movement direction of robot is defined as antibody. According to the biological immune mechanism and the interaction between antigen and antibody, the optimal movement direction angle is calculated and selected. The algorithm also solves the problem of local minimization in the artificial potential field method. The polyclonal artificial immune network algorithm can successfully avoid many static obstacles in the open environment and reach the target position in the optimal path. An improved polyclonal artificial immune network algorithm is proposed to solve the dynamic path planning problem of multiple mobile robots in unknown environments with multiple moving obstacles and moving targets. In addition, a memory unit is introduced to store the environment information that the robot has encountered and the antibodies that respond specifically to the environment. The algorithm can re-select the optimal direction of motion according to the moving obstacle and the real-time location of the moving target. Memory ability can not only increase the specific response but also be selected. The simulation results and analysis show the effectiveness of the algorithm and the superiority of the algorithm compared with other algorithms. (2) A polyclonal artificial immune network algorithm suitable for multi-mobile robot formation planning is proposed in practical application, in order to obtain sufficient environmental information. In complex environment, how to form a suitable formation and maintain, switch different formation and avoid obstacles effectively according to the environment information and the state information of the robot itself from the sensors configured by the multi-mobile robot is a multi-mobile problem. An improved polyclonal artificial immune network algorithm is used to solve the dynamic formation problem of multiple mobile robots in unknown environments with multiple obstacles. The method guarantees the formation of the multi-mobile robot system, maintains the desired formation motion and avoids obstacles. By introducing the graph theory, the smooth switching between the two isomorphic formation is realized and is used to avoid obstacles. When the environment changes, the robot roles and the expected formation can be changed accordingly, and the dynamic formation can be realized. Aiming at the obstacle avoidance, formation formation formation and formation maintenance of the following random robot, different force methods are used to calculate the direction angle and linear velocity of the following random robot from different angles. The position tracking control method is used to calculate the linear velocity of the random robot, which ensures that the position error of the random robot quickly approaches zero and the desired formation is formed. In addition, the asymptotic stability of the whole formation system is proved according to Lyapunov theory. (3) SubVoronoi cell area method for mobile sensor network coverage void detection and repair has important practical significance and wide potential applications: indoor and outdoor cleaning, mine clearance, accident scene search and rescue, farmland sowing and so on. As mobile sensor nodes in sensor networks, all the algorithms for coverage of mobile nodes in sensor networks are applicable to mobile robot coverage. The presence of coverage holes will lead to incomplete perception of monitoring information, affect the connectivity of the network, and even lead to the overall failure of the network, seriously affecting the sensor. Network performance and quality of service. In a limited number of sensor networks, how to detect and repair coverage holes, improve area coverage and node coverage efficiency, and improve the performance of mobile sensor networks is the focus of mobile sensor network area coverage. An algorithm for detecting and repairing coverage voids based on sub-Voronoi cell area method is proposed, which divides each Voronoi cell into several sub-Voronoi cells. According to the geometric relationship between sub-Voronoi cell and node perceptual circle, the coverage void area in each sub-Voronoi cell is calculated, and then it is judged as In order to complete the coverage void repair, the mobile node moves toward the optimal position in the sub-Voronoi cell with the largest void area. The algorithm can not only estimate the location of the void coverage in each Voronoi cell, but also accurately calculate the area of the void coverage in each sub-Voronoi cell. (4) A multi-event dynamic k-coverage planning algorithm for multi-mobile robot systems is proposed, which can be applied to multi-mobile robot monitoring areas. How to minimize the energy consumption is proposed. The problem of multi-event dynamic k-coverage planning in multi-mobile robot systems is studied. It is divided into two sub-problems: uniform distribution of mobile robots and node selection. In order to communicate effectively with static nodes and cover the whole area as much as possible, randomly distributed sparse mobile robots need to be deployed uniformly as possible. Two methods, WSVHG and WSVHI, are proposed to achieve uniform deployment of mobile robots. Then, when events are detected, K mobile robots are selected to cover the events by using game-like theory. The algorithm guarantees that the robot can complete the area coverage with a higher coverage rate and can complete the k-coverage of multi-event with less energy consumption. Simulation results and comparative analysis show that the algorithm is effective.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP242
，
本文編號：2178841
[Abstract]:Through coordinated control, multiple mobile robots can accomplish tasks that a single mobile robot cannot or cannot accomplish: searching for dangerous environments, transporting rescue materials, or enclosing and catching targets. Detection and coverage are the key problems to be solved. In this paper, a series of algorithms are proposed to solve the above-mentioned problems in the coordinated control of multi-mobile robots. The research contents mainly include the following four aspects. (1) A multi-clonal artificial robot for path planning of multi-mobile robots is proposed. Immune network algorithm can quickly and effectively plan a safe collision-free path in complex and dynamic unknown environment according to the environment information obtained by the mobile robot carrying sensors and the state information of the robot itself. It is difficult to obtain the equation and establish the mathematical model of the unknown environment. How to plan the safe path according to the real-time location of obstacles and targets is a difficult problem in the research. The obtained environmental information is defined as antigen, and the possible movement direction of robot is defined as antibody. According to the biological immune mechanism and the interaction between antigen and antibody, the optimal movement direction angle is calculated and selected. The algorithm also solves the problem of local minimization in the artificial potential field method. The polyclonal artificial immune network algorithm can successfully avoid many static obstacles in the open environment and reach the target position in the optimal path. An improved polyclonal artificial immune network algorithm is proposed to solve the dynamic path planning problem of multiple mobile robots in unknown environments with multiple moving obstacles and moving targets. In addition, a memory unit is introduced to store the environment information that the robot has encountered and the antibodies that respond specifically to the environment. The algorithm can re-select the optimal direction of motion according to the moving obstacle and the real-time location of the moving target. Memory ability can not only increase the specific response but also be selected. The simulation results and analysis show the effectiveness of the algorithm and the superiority of the algorithm compared with other algorithms. (2) A polyclonal artificial immune network algorithm suitable for multi-mobile robot formation planning is proposed in practical application, in order to obtain sufficient environmental information. In complex environment, how to form a suitable formation and maintain, switch different formation and avoid obstacles effectively according to the environment information and the state information of the robot itself from the sensors configured by the multi-mobile robot is a multi-mobile problem. An improved polyclonal artificial immune network algorithm is used to solve the dynamic formation problem of multiple mobile robots in unknown environments with multiple obstacles. The method guarantees the formation of the multi-mobile robot system, maintains the desired formation motion and avoids obstacles. By introducing the graph theory, the smooth switching between the two isomorphic formation is realized and is used to avoid obstacles. When the environment changes, the robot roles and the expected formation can be changed accordingly, and the dynamic formation can be realized. Aiming at the obstacle avoidance, formation formation formation and formation maintenance of the following random robot, different force methods are used to calculate the direction angle and linear velocity of the following random robot from different angles. The position tracking control method is used to calculate the linear velocity of the random robot, which ensures that the position error of the random robot quickly approaches zero and the desired formation is formed. In addition, the asymptotic stability of the whole formation system is proved according to Lyapunov theory. (3) SubVoronoi cell area method for mobile sensor network coverage void detection and repair has important practical significance and wide potential applications: indoor and outdoor cleaning, mine clearance, accident scene search and rescue, farmland sowing and so on. As mobile sensor nodes in sensor networks, all the algorithms for coverage of mobile nodes in sensor networks are applicable to mobile robot coverage. The presence of coverage holes will lead to incomplete perception of monitoring information, affect the connectivity of the network, and even lead to the overall failure of the network, seriously affecting the sensor. Network performance and quality of service. In a limited number of sensor networks, how to detect and repair coverage holes, improve area coverage and node coverage efficiency, and improve the performance of mobile sensor networks is the focus of mobile sensor network area coverage. An algorithm for detecting and repairing coverage voids based on sub-Voronoi cell area method is proposed, which divides each Voronoi cell into several sub-Voronoi cells. According to the geometric relationship between sub-Voronoi cell and node perceptual circle, the coverage void area in each sub-Voronoi cell is calculated, and then it is judged as In order to complete the coverage void repair, the mobile node moves toward the optimal position in the sub-Voronoi cell with the largest void area. The algorithm can not only estimate the location of the void coverage in each Voronoi cell, but also accurately calculate the area of the void coverage in each sub-Voronoi cell. (4) A multi-event dynamic k-coverage planning algorithm for multi-mobile robot systems is proposed, which can be applied to multi-mobile robot monitoring areas. How to minimize the energy consumption is proposed. The problem of multi-event dynamic k-coverage planning in multi-mobile robot systems is studied. It is divided into two sub-problems: uniform distribution of mobile robots and node selection. In order to communicate effectively with static nodes and cover the whole area as much as possible, randomly distributed sparse mobile robots need to be deployed uniformly as possible. Two methods, WSVHG and WSVHI, are proposed to achieve uniform deployment of mobile robots. Then, when events are detected, K mobile robots are selected to cover the events by using game-like theory. The algorithm guarantees that the robot can complete the area coverage with a higher coverage rate and can complete the k-coverage of multi-event with less energy consumption. Simulation results and comparative analysis show that the algorithm is effective.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP242
，
本文編號：2178841
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