Robot Path Planning Navigation for Dense Planting Red Jujube Orchards Based on the Joint Improved A* and DWA Algorithms under Laser SLAM

运动规划 计算机科学 算法 雷达 人工智能 激光雷达 机器人 计算机视觉 路径(计算) 遥感 地理 电信 程序设计语言
作者
Yufeng Li,Jingbin Li,Wenhao Zhou,Qingwang Yao,Jing Nie,Xiaochen Qi
出处
期刊:Agriculture [Multidisciplinary Digital Publishing Institute]
卷期号:12 (9): 1445-1445 被引量:19
标识
DOI:10.3390/agriculture12091445
摘要

High precision navigation along specific paths is required for plant protection operations in dwarf and densely planted jujube orchards in southern Xinjiang. This study proposes a robotic path planning and navigation method for dense planting of red jujube orchards based on the improved A* and dynamic window approach (DWA) algorithms using Laser Radar to build maps. First, kinematic and physical robot simulation models are established; a map of the densely planted jujube orchard is constructed using Laser Radar. The robot’s position on the constructed map is described using an adaptive Monte Carlo positioning algorithm. Second, a combination of the improved A* and DWA algorithms is used to implement global and real-time local path planning; an evaluation function is used for path optimisation. The proposed path planning algorithm can accurately determine the robot’s navigation paths, with the average error U, average linear path displacement error, and L-shaped navigation being 2.69, 2.47, and 2.68 cm, respectively. A comparison experiment is set up in the specific path navigation section. The experimental results show that the improved fusion algorithm reduces the average navigation positioning deviation by 0.91cm and 0.54 cm when navigating L and U-shaped specific paths. The improved fusion algorithm is superior to the traditional fusion algorithm in navigation accuracy and navigation stability. It can improve the navigation accuracy of the dense planting jujube garden and provide a reference method for the navigation of the plant protection operation in the densely planted jujube orchards.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
借过123完成签到,获得积分10
刚刚
2秒前
favoury发布了新的文献求助10
3秒前
3秒前
3秒前
favoury发布了新的文献求助10
6秒前
畅快盼望发布了新的文献求助10
7秒前
JayL完成签到,获得积分10
7秒前
动听的谷秋完成签到 ,获得积分10
8秒前
酷波er应助慈祥的涵易采纳,获得10
8秒前
8秒前
9秒前
冰美式发布了新的文献求助10
11秒前
11秒前
SciGPT应助黎_采纳,获得10
11秒前
吴金灿完成签到,获得积分20
13秒前
徐晚疯完成签到,获得积分10
13秒前
科研通AI6.3应助李嘶咩采纳,获得10
13秒前
我是老大应助科研通管家采纳,获得10
14秒前
领导范儿应助科研通管家采纳,获得10
14秒前
bkagyin应助科研通管家采纳,获得10
14秒前
14秒前
14秒前
天天快乐应助科研通管家采纳,获得10
14秒前
所所应助科研通管家采纳,获得10
15秒前
favoury发布了新的文献求助10
15秒前
香蕉觅云应助科研通管家采纳,获得10
15秒前
JamesPei应助科研通管家采纳,获得10
15秒前
完美世界应助科研通管家采纳,获得10
15秒前
FashionBoy应助科研通管家采纳,获得10
15秒前
lu应助科研通管家采纳,获得10
15秒前
打打应助科研通管家采纳,获得10
15秒前
吴金灿发布了新的文献求助10
16秒前
根号五完成签到,获得积分10
16秒前
favoury发布了新的文献求助10
18秒前
FashionBoy应助xiaolizi采纳,获得10
18秒前
ding应助shenjunhong采纳,获得10
18秒前
科研通AI6.2应助moon采纳,获得10
19秒前
小二郎应助瘦瘦安梦采纳,获得10
21秒前
Susi关注了科研通微信公众号
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 2500
Roms fliessende Grenzen : Archäologische Landesausstellung Nordrhein-Westfalen 1000
Atlas of Aligner Treatment and Planning A Case-Based Approach 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7426589
求助须知:如何正确求助?哪些是违规求助? 9029358
关于积分的说明 19234824
捐赠科研通 7054925
什么是DOI,文献DOI怎么找? 3235809
关于科研通互助平台的介绍 2399315
邀请新用户注册赠送积分活动 2218443