胡 煉，王志敏，汪 沛，何 杰，焦晉康，王晨陽，李明錦

·農(nóng)業(yè)裝備工程與機械化·

基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)

胡 煉1,2，王志敏1，汪 沛1,2※，何 杰1,2，焦晉康1，王晨陽1，李明錦1

（1. 華南農(nóng)業(yè)大學南方農(nóng)業(yè)機械與裝備關(guān)鍵技術(shù)教育部重點實驗室，廣州 510642； 2.嶺南現(xiàn)代農(nóng)業(yè)科學與技術(shù)廣東省實驗室茂名分中心，茂名 525000）

為解決基于全球?qū)Ш叫l(wèi)星系統(tǒng)（global navigation satellite system，GNSS）的農(nóng)業(yè)機器人和自動駕駛農(nóng)機在機庫、大棚等衛(wèi)星信號弱或無環(huán)境下定位精度低甚至無法定位的問題，該研究提出了基于激光感知的農(nóng)業(yè)機器人定位方法。采用二維激光雷達和激光接收器設計了基于激光感知的機器人定位系統(tǒng)，通過二維激光雷達發(fā)射掃描激光獲取機器人上激光接收器的點云，同時激光接收器感應掃描激光，融合感應掃描激光時間差和激光接收器點云特征，得到移動激光接收器（即農(nóng)業(yè)機器人）的定位。以全站儀測量為參照在大棚內(nèi)開展驗證試驗，結(jié)果表明，在激光雷達掃描范圍內(nèi)，機器人行駛速度為0.8 m/s時，直線行駛時最大偏差絕對平均值為4.1 cm，最大均方根誤差為1.5 cm；曲線行駛時最大偏差絕對平均值為6.2 cm，最大均方根誤差為2.6 cm，滿足農(nóng)業(yè)機器人在農(nóng)機庫等環(huán)境中自動導航所需定位精度要求。

機器人；激光雷達；激光傳感；定位；智能農(nóng)機裝備

0 引 言

農(nóng)業(yè)機器人通常應用于結(jié)構(gòu)化場景與隨機的不確定場景，且作業(yè)任務日益復雜[1]，定位和導航是農(nóng)業(yè)機器人的關(guān)鍵技術(shù)[2]。當前農(nóng)機自動駕駛技術(shù)和農(nóng)機輔助導航技術(shù)快速發(fā)展[3-7]，通過物聯(lián)網(wǎng)、大數(shù)據(jù)和人工智能等先進信息技術(shù)的聯(lián)合使用，農(nóng)機自動駕駛和輔助導航技術(shù)已在無人化智慧農(nóng)場開始實踐應用[8]。

全球?qū)Ш叫l(wèi)星系統(tǒng)（global navigation satellite system，GNSS）作為農(nóng)業(yè)機械智能化技術(shù)中的一項關(guān)鍵技術(shù)，近年來已被廣泛應用于農(nóng)業(yè)生產(chǎn)各環(huán)節(jié)，其定位精度達到厘米級[9]，基于GNSS的農(nóng)業(yè)機械導航系統(tǒng)旱地作業(yè)直線路徑跟蹤精度優(yōu)于±2.5 cm[4]，水田作業(yè)直線路徑跟蹤橫向偏差平均值為4.3 cm[10]。因此，智能農(nóng)機依靠GNSS定位實現(xiàn)了大田高精度智能化無人作業(yè)[11]，但在農(nóng)機機庫、農(nóng)機轉(zhuǎn)移行駛過程中經(jīng)過樹冠下和高架橋橋底以及溫室大棚設施等場景時，存在GNSS衛(wèi)星信號差或丟失的問題，難以實現(xiàn)導航定位，因此亟需其他定位方法融合補充。

Wi-fi、Zigbee、藍牙和超寬帶等無線通信技術(shù)[12]以及即時定位與地圖構(gòu)建（simultaneous localization and mapping，SLAM）技術(shù)是常用定位方法。無線通信技術(shù)中Wi-fi、超寬帶信號定位易受環(huán)境因素干擾[12-13]，Zigbee和藍牙定位需要鋪設大量設備[14]。SLAM指在沒有環(huán)境先驗信息下，通過使用各種傳感器采集環(huán)境信息，在運動過程中構(gòu)建環(huán)境地圖，并估計機器人位置[15]，目前，已經(jīng)有許多解決SLAM問題的數(shù)學模型與理論基礎[16]。SLAM技術(shù)包括視覺SLAM和激光SLAM，可以提供載體的相對位置信息，定位精度較高，已在物流、工業(yè)、醫(yī)療、安防、服務和農(nóng)業(yè)等移動機器人以及無人駕駛領(lǐng)域廣泛應用[17-21]。在農(nóng)業(yè)機器人出庫入庫時，因庫內(nèi)外光照強度差異大，易導致視覺SLAM定位誤差增大甚至無法定位，而且圖像處理的運算量大、實時性較差[2,22]。此外，當環(huán)境中有較多移動物體時，視覺SLAM的環(huán)境地圖構(gòu)建偏差增大，定位精度降低[23]。相比之下，激光SLAM技術(shù)較成熟、定位誤差更小[24]，但激光SLAM構(gòu)建的地圖缺乏語義信息[25]，對于大場景非固定地圖仍需進一步研究[26]，激光SLAM的地圖構(gòu)建可使用二維激光雷達和三維激光雷達，目前在物流和工業(yè)等領(lǐng)域主要使用成本較高的三維激光雷達[27]。

在無人化農(nóng)場作業(yè)中，若每臺無人駕駛農(nóng)機均配備一套激光SLAM系統(tǒng)和高性能運算處理器實現(xiàn)小范圍衛(wèi)星信號被遮擋區(qū)域內(nèi)的無人駕駛農(nóng)機定位，不僅不能充分利用激光SLAM系統(tǒng)性能，而且增加了成本。因此，在保持現(xiàn)有農(nóng)機無人駕駛系統(tǒng)定位解算算法等前提下，研究能夠和GNSS系統(tǒng)融合補充的定位系統(tǒng)來解決無人駕駛農(nóng)機出入庫衛(wèi)星信號弱或無的問題，對無人化農(nóng)場的研究與建設具有重要意義。故本文設計了基于二維激光感知的農(nóng)業(yè)機器人定位系統(tǒng)，并進行定位試驗驗證其定位精度。

1 基于激光感知的農(nóng)業(yè)機器人定位方法

1.1 基于激光感知的農(nóng)業(yè)機器人定位原理

基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)由移動激光接收器、處理器、固定激光接收器和二維激光雷達組成，如圖1所示，移動激光接收器和處理器安裝在機器人上，固定激光接收器和二維激光雷達固定在已知大地坐標位置，根據(jù)大地坐標點及激光雷達坐標系與大地坐標系的位置關(guān)系，基于激光感知的定位算法計算得到機器人的大地坐標，因此現(xiàn)有農(nóng)機無人駕駛系統(tǒng)的定位解算和控制算法均無需修改即可實現(xiàn)無GNSS信號時實現(xiàn)定位和導航，例如，機器人出庫時，在既有基于激光感知的機器人定位系統(tǒng)定位信號又有GNSS信號的區(qū)域切換GNSS定位系統(tǒng)進行導航，而入庫時，在該區(qū)域切換采用基于激光感知的機器人定位系統(tǒng)進行導航。

圖1 基于激光感知的農(nóng)業(yè)機器人定位原理示意圖

1.2 基于激光感知的農(nóng)業(yè)機器人定位算法

激光雷達以一定周期掃描獲得數(shù)量已知且排序固定的點云數(shù)據(jù)，固定激光接收器感應激光雷達周期性照射產(chǎn)生固定激光信號，且固定激光接收器位置已知，機器人運動過程中移動激光接收器感應激光雷達周期性照射產(chǎn)生移動激光信號，在一個掃描周期中，根據(jù)固定激光信號與移動激光信號得到兩者的觸發(fā)時間差，由此獲得照射到移動激光接收器的激光射線與照射到固定激光接收器的激光射線夾角Δ，以此快速準確找到移動激光接收器在激光雷達點云中的散點集，結(jié)合點云特征匹配算法獲得移動激光接收器中心坐標，最后通過坐標轉(zhuǎn)換得到移動激光接收器中心在大地坐標系中的位置，即農(nóng)業(yè)機器人在大地坐標系中的位置。

在激光雷達掃描平面建立以激光雷達為圓心的極坐標系和直角坐標系，極坐標系中任意點（，），其直角坐標系為（，），坐標轉(zhuǎn)換關(guān)系如下：

由激光接收器光電轉(zhuǎn)換模塊中心坐標推算出移動激光接收器中心坐標，再轉(zhuǎn)換至大地坐標系下移動激光接收器中心坐標，即定位坐標。

注：為接收器外殼長邊長度，cm；為接收器外殼短邊長度，cm；0為接收器感光模塊距外殼短邊距離，cm；0為接收器感光模塊距外殼長邊距離，cm；為接收器感光模塊與坐標原點連線；1為擬合出的接收器外殼長邊所在直線；3為擬合出的接收器外殼短邊所在直線，點為直線1和直線3的交點；2為接收器感光模塊與點連線；、1、2和3分別為直線1、2和3的斜率；1、2和3分別為直線1、2和3的截距。l為離光電轉(zhuǎn)換模塊中心最近的激光雷達掃描射線，θ為激光雷達射線l掃描線對應極坐標的角度值。

Note:is the length of the long side of the mobile laser receiver housing, cm;is the length of the short side of the mobile laser receiver housing, cm;0is the distance from the photosensitive module of the mobile laser receiver to the short side of the housing, cm;0is the distance from the photosensitive module of the mobile laser receiver to the long side of the housing, cm; theis the connection line between the receiver photosensitive module and the coordinate origin, the1is the fitting line of the receiver housing on long side , pointis the intersection of line1and line3,2is the connection line between the photosensitive module of the mobile laser receiver and point, the3is the fitting line of the receiver housing on short side,,1,2and3is the slope of the straight line,1,2and3, respectively;1is the intercept of the straight line1,1is the intercept of the straight line2,3is the intercept of the straight line3, thelis the closest laser radar scanning ray to the center of the photoelectric conversion module,θis the angle value of the polar coordinate corresponding to the scanning line of the laser radar rayl.

圖2 激光接收器光電轉(zhuǎn)換模塊中心坐標幾何關(guān)系示意圖

Fig.2 Schematic diagram of the central coordinate geometric relationship of the photoelectric conversion module of the laser receiver

2 基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)試驗

2.1 系統(tǒng)介紹

基于激光感知的農(nóng)業(yè)機器人定位（ARPLS）系統(tǒng)如圖3所示，以東風井關(guān)T954拖拉機為試驗平臺。ARPLS系統(tǒng)硬件部分主要由移動端和固定端組成，移動端包括移動激光接收器，固定端包括激光雷達和固定激光接收器。激光接收器通過濾光模塊、光電轉(zhuǎn)換模塊、信號調(diào)制模塊將激光雷達發(fā)射的光信號轉(zhuǎn)換成電信號[28]，數(shù)據(jù)處理與通信傳輸模塊將激光感應信號通過CAN總線進行傳輸，激光接收器外殼長邊11 cm，短邊6.5 cm。移動激光接收器安裝在拖拉機頂部機體（沿機頭方向）中心線上，離地高度3 m，激光雷達和固定接收器固定在華南農(nóng)業(yè)大學增城教學科研基地農(nóng)機庫支撐柱上，且移動激光接收器和固定激光接收器均能夠接收到激光雷達發(fā)射的激光射線。移動激光接收器和固定激光接收器的CAN總線通過PCAN-USB傳輸?shù)教幚砥?，PCAN-USB用于監(jiān)聽CAN 網(wǎng)絡消息，時間戳的分辨率為42 μs。激光雷達的測量距離為40～20 000 mm，掃描范圍為270°，角度分辨率為0.117 2°，掃描頻率為10 Hz，誤差為測量距離的1%。

圖3 安裝在拖拉機上的基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)

使用Visual studio 2022通過C#編程語言編寫系統(tǒng)軟件，采用多線程數(shù)據(jù)事件觸發(fā)的方式進行數(shù)據(jù)處理與分析，得到準確的激光雷達、移動激光接收器和固定激光接收器的數(shù)據(jù)響應時間戳，固定端數(shù)據(jù)發(fā)送到移動端進行分析處理，從而實時獲得定位數(shù)據(jù)。

試驗以全站儀和RTK GNSS系統(tǒng)的測量軌跡作為參考對象，且均采用WGS-84坐標系。全站儀自動跟蹤安裝在移動激光接收器上的棱鏡，進行動態(tài)跟蹤測量，全站儀為Leica Ms60，測量頻率10 Hz，100 m范圍內(nèi)測量誤差1 mm；RTK GNSS系統(tǒng)直接測量獲取拖拉機定位，RTK GNSS板卡為K728，測量頻率10 Hz，平面定位精度1 cm。

試驗時拖拉機在激光雷達掃描范圍內(nèi)以0.3、0.5和0.8 m/s分別進行往復的直線運動和曲線運動，行駛距離9～20 m，每組試驗重復5次，ARPLS系統(tǒng)、全站儀和GNSS三套定位系統(tǒng)同時采集定位數(shù)據(jù)，采集時長3～5 min，其中激光感知定位系統(tǒng)每次試驗獲得定位點2 000個以上。

2.2 坐標系轉(zhuǎn)換與機器人中心定位

3 結(jié)果與分析

ARPLS系統(tǒng)、全站儀和GNSS測量的一組拖拉機以0.8 m/s速度直線行駛和曲線行駛的軌跡分別如圖4和圖5所示，其中直線行駛距離10 m、曲線行駛距離12 m。由圖可知，ARPLS系統(tǒng)測量的拖拉機軌跡與全站儀和GNSS測量的軌跡基本重合，表明在試驗行駛距離范圍內(nèi)，ARPLS系統(tǒng)提供了試驗拖拉機在WGS-84坐標系下的定位。

ARPLS系統(tǒng)動態(tài)測量拖拉機以0.8 m/s速度進行直線行駛和曲線行駛定位與全站儀測量定位的偏差絕對值曲線分別如圖6和圖7所示。在相同速度下，直線行駛定位的偏差絕對值明顯小于曲線行駛定位的偏差絕對值，因此，ARPLS系統(tǒng)動態(tài)測量直線運動定位精度高于曲線運動定位精度，測量直線運動定位偏差不大于7 cm，測量曲線運動定位偏差小于12 cm。

圖4 拖拉機直線行駛軌跡

圖5 拖拉機曲線行駛軌跡

圖6 直線行駛的定位偏差絕對值曲線

圖7 曲線行駛的定位偏差絕對值曲線

以全站儀測量定位為真值，各試驗組次ARPLS系統(tǒng)相對全站儀測量定位的偏差絕對平均值和均方根誤差如表1所示。表中試驗數(shù)據(jù)表明，隨著拖拉機速度越快，ARPLS系統(tǒng)定位相對全站儀定位的誤差隨之增大；行駛速度相同時，曲線行駛比直線行駛定位的誤差大。0.8 m/s速度時，直線行駛時最大偏差絕對平均值為4.1 cm，最大均方根誤差為1.5 cm；曲線行駛時最大偏差絕對平均值為6.2 cm，最大均方根誤差為2.6 cm。

表1 激光感知定位相比全站儀定位誤差

ARPLS系統(tǒng)的誤差主要源于移動激光接收器和固定激光接收器感知激光的時間差誤差以及點云擬合誤差。隨著拖拉機速度增加而定位誤差增大是由于激光雷達需要完成一圈掃描才能輸出點云數(shù)據(jù)，導致定位系統(tǒng)數(shù)據(jù)輸出與測量時刻存在延時。曲線行駛定位誤差比直線行駛定位誤差大主要是因為曲線運動導致激光接收器長方形外殼的長邊或短邊點云數(shù)量少甚至沒有，從而降低了算法推算精度。

4 結(jié) 論

1）本文提出了基于激光感知的農(nóng)業(yè)機器人定位方法，利用激光感知和激光雷達點云特征得到移動激光接收器相對固定激光雷達的位置，通過坐標轉(zhuǎn)換獲得機器人的實時大地定位坐標。

2）基于激光感知的定位算法解決了難以從二維激光雷達點云中確定目標對象點云的問題，通過固定激光信號與移動激光信號觸發(fā)時間差快速準確找到移動激光接收器在激光雷達點云中的散點集，結(jié)合點云特征匹配算法實現(xiàn)了快速準確地獲得目標對象定位。

3）設計了基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)，大棚內(nèi)試驗結(jié)果表明，在激光雷達掃描范圍內(nèi)，機器人行駛速度為0.8 m/s時，直線行駛時最大偏差絕對平均值為4.1 cm，最大均方根誤差為1.5 cm；曲線行駛時最大偏差絕對平均值為6.2 cm，最大均方根誤差為2.6 cm。

移動接收器外形以及激光雷達掃描外殼獲得的點云數(shù)量直接影響基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)的定位精度，因此后續(xù)將從大尺寸圓形外殼激光接收器設計、高頻率點云激光雷達選用以及與慣性傳感器融合算法等方面開展研究，進一步提高定位精度和環(huán)境適應能力。

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Agricultural robot positioning system based on laser sensing

HU Lian1,2, WANG Zhimin1, WANG Pei1,2※, HE Jie1,2, JIAO Jinkang1, WANG Chenyang1, LI Mingjin1

(1.,,,510642,; 2.,,525000,)

In order to solve the positioning problem of global navigation satellite system (GNSS) based robots and autonomous agricultural machinery, which is low accuracy or even unable to locate under the environment of weak or no satellite signals such as hangars and greenhouses. This research proposes an agricultural robot positioning system based on laser sensing. The system is designed by using two-dimensional laser scanner and laser receiver, which obtains the point cloud of the laser receiver on the robot through the scanning laser emitted by the two-dimensional laser scanner , and the laser receiver inductively scans by the laser scanner, the location of mobile laser receiver (i.e. agricultural robot) is obtained by fusing the time difference of laser scanning induction and the point cloud characteristics of mobile laser receiver. The agricultural robot positioning system based on laser sensing consists of mobile laser receiver, processor, fixed laser receiver and two-dimensional laser scanner. The mobile laser receiver and processor are installed on the robot, and the fixed laser receiver and two-dimensional laser radar are fixed at the known geodetic coordinate position. According to the position relationship between the laser scanner coordinate system and the known geodetic coordinate system. The laser scanner scanning at a certain period to obtain a known number of fixed-order point cloud data. The fixed laser receiver senses the periodic irradiation of the laser scanner to generate the base station laser signal, and the serial number of the fixed laser receiver shell in the point cloud is known. The mobile laser receiver senses the periodic irradiation of the laser radar to generate the mobile laser signal during the movement of the robot. According to the trigger time difference between the fixed laser signal and the mobile laser signal, the angle between the laser rays that are irradiated to the mobile laser receiver and the laser rays that are irradiated to the fixed laser receiver can be obtained in a scanning period of the laser scanner. And the scattered point set of the mobile laser receiver in the laser radar point cloud can be found, and the center coordinate of the mobile laser receiver can be obtained by combining the point cloud feature matching algorithm. The robot positioning can be calculated by combined with the geodetic coordinates of the laser scanner and the position relationship between the laser scanner coordinate system and the geodetic coordinate system, the central coordinates of the mobile laser receiver under the geodetic coordinate system. The geodetic coordinates of the robot are calculated by the positioning algorithm based on laser sensing, and the geodetic coordinates of the robot without GNSS signal are supplemented without changing the positioning solution and control algorithm of the existing robot unmanned system. For example, when the robot leaves the hangar, it switches to the GNSS positioning system for positioning and navigation in the area with both the positioning signals of the robot positioning system based on laser perception and the GNSS signal. When entering the hangar, switch to the robot positioning system based on laser sensing for positioning and navigation in the area cover with both the positioning signal of the robot positioning system based on laser perception and the GNSS signal. The verification test is carried out with the reference of total station which shows that within the scanning range of laser radar, when the robot is at a speed of 0.8 m/s, the absolute average value of the maximum deviation of the positioning error in a straight line is 4.1 cm, and the maximum root mean square error is 1.5 cm; when the robot driving on a curve, the absolute average value of the maximum deviation of positioning error is 6.2 cm , and the maximum root mean square error is 2.6 cm. The result shows that this method can achieve accurate robot positioning and meets the positioning accuracy requirements for automatic navigation of agricultural robots in agricultural machinery warehouses and other environments.

robot; laser radar; laser sensing; positioning; intelligent agricultural machinery equipment

10.11975/j.issn.1002-6819.202211144

S24; TP273

A

1002-6819(2023)-05-0001-07

胡煉，王志敏，汪沛，等. 基于激光感知的農(nóng)業(yè)機器人定位系統(tǒng)[J]. 農(nóng)業(yè)工程學報，2023，39(5)：1-7.doi：10.11975/j.issn.1002-6819.202211144 http://www.tcsae.org

HU Lian, WANG Zhimin, WANG Pei, et al. Agricultural robot positioning system based on laser sensing[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2023, 39(5): 1-7. (in Chinese with English abstract) doi：10.11975/j.issn.1002-6819.202211144 http://www.tcsae.org

2022-11-14

2023-01-16

江蘇大學農(nóng)業(yè)裝備學部項目（NZXB20210106）；廣東省科技計劃項目（2021B1212040009）；佛山市科技創(chuàng)新項目（2120001008424）；國家現(xiàn)代農(nóng)業(yè)技術(shù)體系（CARS-13）

胡煉，博士，研究員，研究方向為智能農(nóng)機裝備和無人農(nóng)場。Email：lianhu@scau.edu.cn

汪沛，博士，講師，研究方向為農(nóng)業(yè)工程、精準農(nóng)業(yè)研究。Email：wangpei@scau.edu.cn