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摘要: 針對非結構環境下高速公路綠籬修剪機器人手臂實時準確避障問題, 提出一種基于擾動人工勢場法的避障路徑規劃解決方法.根據綠籬隔離帶與障礙物分布情況, 設計智能修剪機器人執行機構, 構建包絡障礙物簡化模型, 分析機械臂與障礙物的碰撞條件, 求解機械臂在修剪過程中的避碰空間.引入斥力場調節策略來優化勢場模型, 建立斥力場擾動機制調整斥力影響方式, 消除傳統算法中的局部極小點、目標不可達等現象.在避碰空間內, 應用擾動人工勢場法對機械臂進行路徑規劃仿真, 仿真結果表明, 機械臂跳出局部極小點, 靈活順利避障, 成功抵達目標點, 驗證了該方法的有效性和可行性.Abstract: Expressway hedgerow pruning robots need be able to recognize hedgerow and position themselves real-time, to plan an obstacle avoidance trajectory from the starting point to target point based on the position relationship between hedgerows and obstacles. Compared with the traditional industry manipulator, the expressway hedgerow pruning robot manipulator frequently works in unstructured environments with unknown obstacles and irregular scales. It is difficult to establish a mathematical model of obstacles precisely and comprehensively. The problem of real-time obstacle avoidance can be solved by path planning. Thus, aiming at the problem of real-time obstacle avoidance for expressway hedgerows pruning robot manipulator in an unstructured environment, a novel path planning method to avoid obstacle based on perturbed artificial potential field (PAPF) was proposed. According to the distribution of hedgerows and obstacles, simplified models of intelligent pruning robot and sphere enveloping obstacle were established. By considering the geometric relationship between manipulator and obstacle, the collision conditions of manipulator and obstacles were analyzed, and then, the collision avoidance space of manipulator was solved. The traditional artificial potential field method was associated with some problems such as local minimum point (LMP) and goals nonreachable with obstacles nearby(GNRON). In this study, a repulsion field adjustment strategy was presented to optimize the function model of potential field, and a repulsion field perturbation mechanism was introduced to adjust the effect of repulsion in order to flexibly avoid obstacles and successfully reach the target point. The path planning simulation of the designed manipulator was carried out in the collision avoidance space using PAPF. The simulation result shows that the manipulator smoothly jumps out of the LMP and reaches the target point successfully by accurately avoiding obstacles in real time, which verifies the effectiveness and feasibility of the proposed method.
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圖 1 修剪機器人結構簡圖
1—輪式小車；2—回轉臺；3—控制板電源箱；4—伺服電機；5—諧波減速器；6—傳動軸；7—腰部；8—大臂；9—小臂；10—腕部；11—修剪電機；12—多傳感器系統刀具盤；13—減速齒輪組；14—回轉刀具
Figure 1. Structure of pruning robot
圖 7 機械臂避障規劃仿真效果圖. (a) 實驗一人工勢場算法；(b) 實驗一擾動人工勢場算法；(c) 實驗二人工勢場算法；(d) 實驗二擾動人工勢場算法；(e) 實驗三人工勢場算法；(f) 實驗三擾動人工勢場算法
Figure 7. Path planning simulation for manipulator: (a) APF algorithm in Test 1; (b) PAPF algorithm in Test 1; (c) APF algorithm in Test 2; (d) PAPF algorithm in Test 2; (e) APF algorithm in Test 3; (f) PAPF algorithm in Test 3
圖 8 機械臂運動關節參數變化圖. (a) 實驗一關節角；(b) 實驗一關節角速度；(c) 實驗二關節角；(d) 實驗二關節角速度；(e) 實驗三關節角；(f) 實驗三關節角速度
Figure 8. Motion parameters of manipulator joints: (a) angle of joint in Test 1; (b) angular velocity of joint in Test 1; (c) angle of joint in Test 2; (d) angular velocity of joint in Test 2; (e) angle of joint in Test 3; (f) angular velocity of joint in Test 3
表 1 修剪機械臂D-H連桿參數
Table 1. D-H link parameters of pruning manipulator
連桿序號，i 長度，
ai-1/m扭角，
αi-1/(°)偏置，
di/m關節角，
θi/(°)變量范圍，
/(°)1 0 0 0.5 θ1 -160~160 2 0 -90 0 θ2 -225~45 3 1.3 0 0 θ3 -150~120 4 1.7 0 0 θ4 -210~30 5 0 -90 0 θ5 -180~180 
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表 2 算法基本參數設置
Table 2. Basic parameter setting of the algorithm
引力增益尺度因子，ka 斥力增益尺度因子，kb 斥力場作用半徑，ρb/m 距離尺度因子系數，n 斥力偏轉角，?/(°) 步長，l/m 最大循環迭代次數，N 1 2 0.5 2 30 0.1 50
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